Multimedia forensics is a promising technique in authenticating an unknown source for the trustworthiness of the multimedia content. On the other hand, multimedia anti-forensics is also crucial in such a way that the weakness of a known detector can be investigated. Our work aims at the anti-forensic of median filter. Median filter distorts the distribution of pixel differences in an image and our work focuses on shifting the statistics of the pixel difference back to an estimate of the original image. We first model the distribution of the pixel differences as generalized Gaussian distribution. After extracting the parameters of the generalized Gaussian distribution, a plausible parameter of distribution of the original image can be estimated. Noise is added to the pixel difference to push the statistics of pixel differences back to the estimated one to conceal the trace of median filtering.

In a multi-cell environment, if a base station transmits data to its own users without considering the interference caused to neighboring cells. The inter-cell interference may limit the transmission rates of all links. In this work, we consider the game theory approach to design the downlink beamformers. Given the target SINR requirement at each links and the transmit power constrain, each transmitter determines its optimal downlink beamforming strategy to maximize its own rate. Numerical results show that proposed game performs better than the present rate game with transmit power constrain only. Both the link average rate and the worst case rate can be enhanced with proper SINR threshold.

For multi-user relay system, the network coding principle has been actively implemented due to its advantage in alleviating the spectral efficiency loss. Previously, in the well-known physical-layer network coding and denoise-and-forward strategies, the relay maps different input signal pairs to the same output message, e.g., both (+1,-1) and (-1,+1) are mapped to +1. Thus, the destination confronts detection ambiguity since it can only depend on the direct link transmission. Consequently, the aforementioned strategies cannot achieve full diversity.To solve such detection ambiguity problem, we propose a new relay mapping strategy for the two-user multiple-access relay channel, where the received signal at the relay is mapped to the 4-ary pulse amplitude modulation signal to avoid the ambiguity issue. Based on the instantaneous relay constellation and destination constellation, we derive the decision regions for different source symbols and obtain the detection error rates at both the relay and destination in closed form, which are shown to be in tight match with Monte-Carlo simulation results. Furthermore, to achieve the full diversity, we implement the link adaptive regenerative (LAR) strategy, where relayed symbols are scaled before being forwarded to the destination. Finally, to minimize the error performances, we further propose a scheme based on maximizing the minimum Euclidean distance of any adjacent constellation points at the destination. Simulations show that our method can achieve similar performances as exhaustive search while greatly simplifying the computations.

Due to the ease of tampering digital signals, the authenticity of the acquired signal becomes even more concerned, and lots of forensic techniques have been proposed to adapt to various forgery concerns. Among them, acquisition forensics plays an important role to identify the acquisition process of a signal and verify its authenticity. Recently, a new acquisition technique - compressive sensing - has been broadly studied in many applications for its much lower sampling rate than traditional uniform sampling schemes. Yet, few work has been done in acquisition forensics to take this promising technique into account, i.e., to identify the image been compressive sensed or not. In this talk, we will propose general compressive sensing detectors regardless of what particular signal this technique applies to. Specifically, we propose two detection schemes according to how much information we have about the distribution model of the signal or noise. Moreover, we also propose an estimator for the number of measurements used in compressive sensing. Substantial simulations show our detector and estimator performance with respect to every aspect.

Network coding has been widely used in the wireless uplink to improve the throughput and provide the spatial diversity. However, the receiver has to estimate the channel coefficients of all users to perform coherent detection, thus the signaling overhead is sometimes formidable and may even outweigh the performance gain. To reduce the channel estimation overhead, we study the non-coherent frequency-shift keying modulations in this work with emphasis on receiver design and performance analysis. Depending on the available channel state information (CSI), we first develop the coherent and non-coherent receivers based on the maximum likelihood (ML) principle for both the analog network coding (ANC) and digital network coding (DNC). As the ML receiver of non-coherent ANC has a non-tractable integral form, we further propose two suboptimum receivers depending on the relative link quality of the source-relay channel and relay-destination channel. We also study the pair-wise error probability of ANC and DNC, and show that the full diversity is still achievable using non-coherent modulations; however, some additional logarithmic term loss would be introduced in the error rate expressions. We demonstrate that the performances loss is much more significant for ANC due to the incapability to efficiently suppress the multi-user interferences. Extensive simulations are also given to verify our analytical results.

In an admission control game, users decide which one of the two cellular cells to enter by maximizing their expected rewards. The immediate reward of each user in a cell decreases as the number of users in the cell increases. When a user aims to maximize his expected reward, his optimal decision depends on the others' decisions. In this work, we formulate the problem of finding the optimal decision rule as a Markov Decision Process (MDP) and propose a modified value iteration algorithm which can efficiently obtain the optimal decision rule. The analysis of the proposed algorithm shows that the optimal decision rule has a simple threshold structure. Numerical simulation results validate the analysis and demonstrate the effectiveness of the optimal decision rule.

In the opportunistic spectrum access model of cognitive radio networks , secondary users (SUs) are allowed to exploit the licensed channels only when the primary users (PUs) are absent. Moreover, SUs usually need to share the available licensed channels. However, due to hardware limitation and imperfect detection, how can the SU obtain accurate information about the true system state, and furthermore, make right decision of accessing a channel to avoid competitions from huge crowds in the same channel, remains a challenge to fully utilize the scare spectrum resources. In this paper, considering a scenario where SUs sense the channels simultaneously and make access decisions sequentially, we model the SUs' decision making process as a Chinese restaurant game. In the proposed game, the SU builds its knowledge of the system state by sensing one of the channels and learning information such as signals and decisions revealed by the previous SUs. It also predicts the decisions of the subsequent SUs to maximize the utility. We analyze the interactions of SUs in the proposed game, specifically, the impact of initial belief, sensing accuracy and the channel quality on SUs' decisions. Some important theoretical conclusions for the two-user two-channel scenario are derived. We finally verify our theoretical conclusions and prove the effectiveness of the proposed scheme through simulation results.

As we discussed last time, the world-wide cellular networks of today consume a considerable amount of electric power. The energy consumption of cellular networks accounts for near 50% of the operational expenses of cellular service providers. On the other hand, there exists substantial potential through cooperative communications and smarter network operations to save energy. Based on our previous work, we go a step further in our recent work by trying to answer two important questions: 1. What is the condition under which we could switch-off some cells? 2. Which switch-off pattern could maximize overall energy-saving performance under various traffic load demands? In this work, we propose an energy-efficient switching strategy that considers the daily traffic demand profile. We use cooperative communications to extend service from working ("Sun") cells to the switched-off ("Moon") cells with guaranteed quality of service (QoS). We take into account both the call-blocking probability and the combined channel outage probability as the metrics of QoS. Power-saving is maximized among all proposed patterns without compromising the bottom-line QoSs. Both analytical results and numerical evaluations show that the proposed strategy presents great potential of energy saving.

In today’s talk, I will present some recent progress on our resource sharing game project. The resource sharing game is proposed to model the interactions among a group of rational players who share limited resources with unknown statistics, and can find applications in many areas, such as broadband wireless communications, online advertisement and etc. In this game, players will need to predict other players?decisions as well as to learn the statistics of resources in order to maximize their expected utilities. We will show, in this talk, a recursive algorithm that can find an action profile that is a subgame perfect equilibrium of the proposed game. The design of learning rules will also be discussed in today’s presentation.

Dynamic spectrum access in cognitive radio networks can greatly improve the spectrum utilization efficiency. Nevertheless, interference may be introduced to the Primary User (PU) when the Secondary Users (SUs) dynamically utilize the PU’s licensed channels. If the SUs can be synchronous with the PU’s time slots, the interference is mainly due to their imperfect spectrum sensing of the primary channel. However, if the SUs have no knowledge about the PU’s exact communication mechanism, additional interference may occur. In this paper, we propose a dynamic spectrum access protocol for the SUs confronting with unknown primary behavior and study the interference caused by their dynamic access. Through analyzing the SUs?dynamic behavior in the primary channel which is modeled as an ON-OFF process, we prove that the SUs?communication behavior is a renewal process. Based on the Renewal Theory, we quantify the interference caused by the SUs and derive the corresponding close-form expressions. With the interference analysis, we study how to optimize the SUs?performance under the constraints of the PU’s communication quality of service (QoS) and the secondary network’s stability. Finally, simulation results are shown to verify the effectiveness of our analysis.

In a social network, agents are intelligent and have the capability to make decisions to maximize their utilities. They can either make wise decisions by taking advantages of other agents' experiences through learning, or make decisions earlier to avoid competitions from huge crowds. Both these two effects, social learning and negative network externality, play important roles in the decision process of an agent. We propose a new game, called Chinese Restaurant Game, to formulate the social learning problem with negative network externality. Through analyzing the proposed Chinese restaurant game, we derive the optimal strategy of each agent and provide a recursive method to achieve the optimal strategy. How social learning and negative network externality influence each other under various settings is also studied through simulations. Finally, we illustrate how the proposed framework can be applied to many problems in different research fields, such as wireless networking, cloud computing and online social networking.

Compressive sensing is a promising technique which realizes a sub-Nyquist sampling rate for sparse and nearly sparse signals. Many applications have been studied and implemented for all kinds of sparse signals, such as images, radar, cognitive radio and so on, either for lower sampling or denoising purpose. However, little work has been done on acquisition forensics regarding this new technique. In this talk, I'll present our work on compressive sensing forensics to distinguish those noisy sparse or nearly sparse signals obtained by compressive sensing from those acquired using uniformly Nyquist sampling technique. Specifically, we categorize the feasible signals for compressive sensing into noisy sparse and nearly sparse signals. And propose the detection scheme for each model under different assumptions of the signal knowledge we got. In addition, the estimation of number of measurements is also proposed for noisy sparse signal with simulation done to see the performance.

We study the error performance of the multiple-access relay channel using amplify-and-forward protocol. Both of the variable gain relaying (VGR) and fixed gain relaying (FGR) are studied, where the relay nodes are subject to short-term power constraint and long-term power constraint, respectively. For the single-relay system, we show that both of VGR and FGR can achieve a diversity order of (2,-1), and the pairwise error probability (PEP) increases linearly with the number of sources (i.e., K). When there are multiple relays (i.e, L), we propose a relay selection scheme to minimize the maximum PEP, and show that the diversity order is (L+1,-L). To improve the coding gain, we then study the distributed space-time block coding (DSTBC). We prove that DSTBC-FGR can always achieve full primary diversity, whereas the diversity of DSTBC-VGR is upper bounded by min (L+1,K+1). For the single-source network, we then develop a selective DSTBC-VGR scheme by adaptively allocating the relay power, and we show that the diversity is (L+1,0). Finally, we study the diagonal distributed space-time coding (DDSTC). We show that the diversity is (L+1,-L) for both of DDSTC-VGR and DDSTC-FGR, and the code design criterion is to maximize the minimum product distance.

Over the past decade, researchers have developed a variety of digital forensic techniques to verify the authenticity and trace the processing history of digital multimedia files. While forensic techniques have been traditionally viewed as a tool to prevent and detect the falsification of digital multimedia content, this does not mean that they cannot be used for malicious purposes. For example, digital forensic techniques can possibly be used to reverse engineer proprietary signal processing components inside digital devices. In this talk, we show how anti-forensics can be used to provide information security in situations when forensic tools can be abused. Specifically, we propose an anti-forensic module that can be integrated into a digital camera’s signal processing pipeline to prevent the reverse engineering of its color filter array and color layer interpolation technique.

In this work, we consider the non-codebook-based precoder design problem for multi-user MIMO downlink with per antenna power constraints in LTE-Advanced systems. The Maximum SINR filter is applied to maximize the criterion of sum SINR for the jointly encoded multiple data streams within a user. It has been shown that such a criterion makes the joint decoding become close to ML decoding. The proposed algorithm utilizes Lagrangian duality to solve for the precoders with the primal-dual method. Simulation results demonstrate that the proposed algorithm significantly outperforms other conventional methods such as zero-forcing (ZF), block-diagnalization (BD), and signal-to-leakage-and-noise ratio (SLNR).

Compression of encrypted data is becoming an active research topic in recent years. The traditional way of securely and efficiently transmitting redundant data is to first compress the data to reduce the redundancy, and then to encrypt the compressed data to mask its meaning. At the receiver side, the decryption is performed before prior to decompression. However, in some application scenarios, a sender needs to transmit some data to a receiver and hopes to keep the information confidential to a network operator who provides the channel resource for the transmission. The sender should encrypt the original data and the network provider always has interest in reducing the data rate, and may tend to compress the encrypted data without any knowledge of the cryptographic key and the original data. At receiver side, a decoder integrating decompression and decryption functions will be used to reconstruct the original data. In this talk, a novel scheme for scalable lossy compression for encrypted image using stream cipher and the primary results will be presented.

Several previous works have demonstrated that to optimize the performance of iterative maximum a posteriori probability (MAP) decoder for turbo codes, it is crucial to estimate the channel signal-to-noise ratio (SNR) within the iterative MAP turbo decoder. In this talk, we investigate the behavior of the iterative MAP turbo decoder under the channel SNR estimation error and propose a new channel reliability value (CRV) for iterative MAP turbo decoder. Unlike the traditional CRV, the proposed CRV is not a function of channel SNR. Hence, it is not required to estimate the channel SNR within the iterative MAP turbo decoder and thus it simplifies the decoder implementation. Simulation results show that the iterative MAP decoder employing the proposed CRV provides better error performance compared to the traditional iterative MAP decoder.

The rising cost of energy and increased environmental awareness have sparked a keen interest in the development and deployment of energy-efficient communication technologies. The energy efficiency of cellular networks can be increased significantly by selectively switching off some of the base stations (BSs) during periods of low traffic load. In this paper, we propose a scalable BS switching strategy and use cooperative communication techniques and power control to extend network coverage to the service areas of the switched-off BSs. The outage probability and the achievable power savings of the proposed scheme are analyzed, both analytically and numerically, and a potential of up to 50% power saving is observed in the numerical results.

Dynamic spectrum access is a promising technique enabling the efficient usage of the limited spectrum. In the scenario when a primary user is far away from the base station and is experiencing low achievable rates while some secondary users half way between the primary user and the base station and has more favorable channel conditions, how can we utilize the spectrum so that we can improve the QoS of PU while assign SU the chance to access the vacant spectrum? In this work, we propose a novel spectrum sharing model considering the fair and efficient allocation of both used and unused channels and incorporate indirect reciprocity game to stimulate the cooperation between primary and secondary users to improve the overall system performance. We develop a reputation updating policy under time-vary channel and show the existence of stationary reputation distribution for any given optimal action rule. We also theoretically derive the stable condition of the optimal action rule.

The viability of cooperative communications largely depends on the willingness of users to help. However, in future wireless networks where users are rational and pursue different objectives, they will not help to relay information for others unless this can improve their own utilities. Therefore, it is very important to study the incentive issues when designing cooperative communication systems. In this paper, we propose a cooperation stimulation scheme for multiuser cooptative communication networks using indirect reciprocity game. By introducing the notion of reputation and social norm, users care about their future utilities and get the incentive to cooperate with others. Different from existing works on reputation based schemes that mainly relay on experimental verifications, we theoretically demonstrate the effectiveness of our scheme in two steps. First, we conduct steady state analysis of the game and show that cooperating with users having good reputation can be sustained as an equilibrium. Then, by modeling the action spreading at the transient state as an evolutionary game, we show that the equilibriums we found are stable and can be reached with proper initial conditions. Moreover, we deal with possible cheating behaviors of users through the introduction of energy detection. Finally, simulation results are shown to verify the efficiency and effectiveness of the proposed scheme.

Social learning, which agents learn knowledge from other agents' behaviors and shared information, is a trending topic in the research of social networks. In traditional social learning problem, the payoff of a player depends only on his own action and the unknown state. The externality from other players' actions is seldom discussed, especially the negative effect due to competition from other players. In this work, we proposed the Chinese restaurant game as a new game to analyze users¡¯ competition behaviors in social networks with social learning characteristics. In this early report, we analyzed the equilibrium in simultaneous game with perfect/imperfect signals. We also derived the best response and equilibrium in sequential game in recursive form.

To prevent the spread of digital forgeries, a variety of digital forensic techniques have been developed to detect manipulations made to multimedia content. In response, both forgers and forensics researchers have developed a number of anti-forensic operations designed to fool digital forensic techniques. This situation is further complicated by the fact that anti-forensic operations can leave detectable traces in digital content, allowing forensic investigators to develop techniques capable of detecting the use of anti-forensics. As a result, digital forgers and forensic investigators must respond to each other¡¯s actions in order to achieve their goals (i.e. creating undetectable forgeries and detecting digital forgeries respectively). In this talk, we investigate the interplay between the actions of a forger and forensic investigator. We discuss how to evaluate the performance of forensic and anti-forensic algorithms in the presence of opposing forensic and anti-forensic techniques. Additionally, we use game theory to identify the optimal strategies employed by the forger when using anti-forensics and the forensic investigator when attempting to detect forgeries. We use our recently proposed video frame deletion forensic and anti-forensic algorithms to perform a case study of these new techniques.

Network coding has been widely used in wireless uplink to improve spectral efficiency. However, the relay decoding error may propagate to the intended receiver and thus severely degrade the diversity performance. So in this work, we develop two power scaling schemes at the relay side and two detection schemes at the receiver side, respectively, to mitigate error propagation and thus achieve full diversity. For the soft power scaling based link adaptive relaying, we develop a virtual source-relay-destination channel model and demonstrate that the relay power should be such to balance the signal-to-noise ratios of the source-relay channel and relay-destination channel. As for the hard power scaling based ON-OFF relaying, we first design a decision rule based on total pairwise error probability, and then simplifies it to the threshold-based relaying strategy. At the receiver side, we show that the weighted minimum distance detection with the weight being determined by the relative link quality of source-relay channel and relay-destination channel can achieve full diversity once the global channel state information is available, otherwise the maximum likelihood detection that explicitly takes into account relay decoding error should be employed to achieve full diversity. Finally we compare these schemes in terms of relay power consumption and signalling overhead, and validate our results through simulations.

Image forensic algorithms of tracing an image's processing history has been well studied regarding traditional compression, like JPEG and JPEG2000. However, little consideration has been given to a recent technique - compressive sensing, with which we can acquire the compressed data by directly sensing the objects, like single-pixel camera. In this talk, we show that compressive sensing, like other traditional compression methods, also leave fingerprint on the data of the image in wavelet domain. We also propose a two step detection to distinguish the fingerprint come from different compressions, and further tell whether an image has been compressive sensed.

Within the past decade, the proliferation of multimedia social network communities, such as Napster, and YouTube where millions of users form a dynamically changing infrastructure to share content, have introduced the new concept of social networking that creates a technological revolution as well as brings new experiences to users. The massive content production poses new challenges to the scalable and reliable sharing of multimedia content over large and heterogeneous networks. It also raises critical issues of intellectual property protection and privacy issues. In a multimedia social network, users actively interact with each other, and such user dynamics not only influence each individual user but also affect the system performance. To provide a predictable and satisfactory level of service, it is of ample importance to understand the impact of human factors on multimedia social networks. Such an understanding provides fundamental guidelines to the better design of multimedia systems and networking, and offers more secure and personalized services. For example, in a peer-to-peer file-sharing system, users pool together the resources and cooperate with each other to provide an inexpensive, highly scalable, and robust platform for distributed data sharing. However, since the nature of participation in many multimedia social networks is often voluntary and unregulated, there is a need to provide incentives and mechanism to stimulate cooperation among users to improve system performance. This talk will illustrate various aspects of issues and problems in multimedia social networks via two case studies of human behavior in multimedia fingerprinting, peer-to-peer live streaming, and mobile video sharing.

Jamming-resistant broadcast is important for many safety-critical applications such as emergency alert broadcast and navigation signal dissemination, and is critical for the distribution of important information such as the public key and system control information in wireless systems. Spread spectrum techniques have been commonly adopted to counteract jamming, based on the pre-shared secretes (such as spreading codes in DSSS or frequency hopping pattern in FH) at the senders and legitimate receivers. This requirement suffers from scalability concerns, and may not even be feasible in the face of network dynamics and compromised receivers. This problem was recognized recently, leading to a series of promising research efforts, including Uncoordinated FH (UFH) techniques and Uncoordinated DSSS (UDSSS). Unfortunately, these techniques still suffer from low communication efficiency. For example, the relative throughput of the original UFH compared with coordinated FH is only on the order of 10^{-3} for a spreading ratio of 200. Therefore, we propose a Collaborative UFH-based Broadcast (CUB) scheme to achieve higher efficiency and stronger jamming resistance than existing anti-jamming broadcast schemes. The main idea is to allow the set of nodes that already receive the message to help broadcast, as all the nodes are expecting the same broadcast message. This process may start slowly, but as more and more nodes join the relaying, the broadcast accelerates much like an avalanche. This scheme exploits the node cooperation to enhance both the efficiency and the security. Unless all the channels are simultaneously blocked (assumed impossible for a fairly large spreading ratio), it is always possible for some nodes to obtain the message through unjammed channels. These nodes then relay it across more channels to increase the success rate of reception. With time on its side, our scheme is fundamentally more powerful than most recent attempts for anti-jamming broadcast. In addition, this approach is not restricted to UFH, and can be readily combined with other jamming counter measures. We provide three relay channel selection strategies for collaborative broadcast, analyze the corresponding successful packet reception rates for both synchronous and asynchronous scenarios, and present the corresponding cooperation gain. Simulation results in a practical setting show that our scheme significantly reduces broadcast delay and energy consumption against the most powerful jamming. For example, compared with the non-collaborative UFH-based broadcast scheme, the proposed scheme takes only 14% of time to complete the broadcast in a 100-node wireless network against 20 responsive-sweep jammers.

While demand response has achieved promising results on making the power grid more efficient and reliable, the additional dynamics and flexibility brought by demand response also increase the uncertainty and complexity of the centralized load forecast. In this talk, we propose a game theoretic demand response scheme that can transform the traditional centralized load prediction structure into a distributed load prediction system by the participation of customers. Moreover, since customers are generally rational and thus naturally selfish, they will cheat if cheating can improve their payoff. Therefore, enforcing truth-telling is crucial. We prove analytically and demonstrate with simulations that the proposed game theoretic scheme is cheat-proof, i.e., all customers are motivated to report and consume their true optimal demands and any deviation will lead to a utility loss.

This talk discusses starts by discussing Hawaii's energy landscape and the REIS program. The state of Hawai'i and the US Department of Energy (DOE) signed a memorandum of understanding in 2008 known as the Hawaii Clean Energy Initiative (HCEI) requiring 70% of Hawaii's energy come from clean sources by 2030. At the beginning of 2009 we formed a multidisciplinary research and education program at the University of Hawai'i at Manoa, (REIS) to focus on renewable energy, sustainability, and smart grids. The REIS group won an internal UHM sustainability competition in 2009 and in 2010 won a DOE work force training grant in the Strategic Training and Education in Power Systems. We discuss goals of our group including building the REIS program, research and education activities, and interfacing with other UHM sustainability efforts, outside academic institutions, industry, and government. We then discuss some recent work in the smart grid area. We propose modeling micro-grid parameters using probabilistic formulations. A goal is to model the micro-grid beyond the last substation including distributed generation sources (wind and solar). The micro-grid will have measuring devices such as AMI at some locations. We model the micro-grid as a factor graph and use belief propagation to perform inference on the grid. A goal is to estimate parameters using message passing and then use this information to perform control and security on the micro-grid.

A new cooperative transmission protocol and network coding scheme for synchronized multi-source system are proposed. The users are organized in two groups. Users in separate groups transmit in separate time slots. Users in the same group transmit with orthogonal waveforms. In each transmission, the user transmits his own information and relays other users¡¦ information at the same time. The proposed protocol is able to mimic the full-duplex transmission with half-duplex mode to achieve high data rate. The network code for this protocol can be designed using classical linear block code. It is shown that the minimum Hamming distance of the network code determines the system diversity order. Therefore, with well-designed network code, the proposed protocol can achieve high diversity order. Simulation results demonstrate its superior performance compared with previous work.

Cooperative peer-to-peer (P2P) streaming, which enables cooperation among geographically neighboring peers with large intra-group bandwidth, is regarded as a promising approach to address the network inefficiency problem encountered by the traditional non-cooperative P2P schemes. However, due to the selfish nature of peers, they may tend to report false private information in order to act as free-riders, which consequently leads to a substantial system inefficiency. In this talk, we propose a mechanism design based cooperative P2P streaming scheme which achieves the optimal system-wide streaming performance. In particular, with properly designed transfer function, we show that it is a dominant strategy for each user to participate in the cooperative streaming and report their private information truthfully. Moreover, in the proposed scheme, the transfer is proved to exchange only within the group without surplus or deficit at any time.

Wireless Green Communication technology has long been desired with today’s fast expansion of wireless infrastructures and applications throughout the world. In seeking of novel wireless green communication technologies, we discovered that the time reversal (TR) transmission technique can be a promising candidate, due to its inherent capability of efficiently harvesting signal energy from the multipath environment and its low complexity.

In this talk, we take a closer look at the essence of the time reversal structure and its fundamental theoretical limits. As will be shown in the first part of this talk, the time reversal structure tends to be dedicated to system reliability by maximizing the energy-efficiency and diversity order (through time-domain processing), compared with its counterpart OFDM (mostly frequency-domain processing) in favor of high multiplexing order as another extreme.

Based on this observation, it would be interesting and important to investigate whether a desirable tradeoff between the two benefits can be obtained by an innovative system design. In the second part, we introduce a multi-band time reversal structure that can achievable arbitrary tradeoff between the benefits that are otherwise exclusively possessed by single-band TR and OFDM. Besides, the multi-band structure allows added flexibility, such as multi-hopping, multiple access, resource allocation, security and regulatory spectrum operation.

To summarize, the time-reversal (single/multiple band structures) is an ideal candidate for (very) wideband wireless green communications where energy-efficiency, reliability and interfering/informational leakage are the primary concerns, compared with the spectrum efficiency.

Constrained matrix factorization has become widely popular for performing tasks in music information retrieval (MIR) such as music transcription and source separation. However, the basic formulations of these factorization algorithms have trouble decomposing particular types of musical data. Recent developments in factorization techniques that exploit the sparsity or nonnegativity of data have improved the effectiveness of these factorizations. Nevertheless, the sophistication and efficiency of these methods must keep up with the growing size and complexity of the data around us.

In this dissertation, I propose methods for sparse and nonnegative factorization that is specifically suited for analyzing musical signals. First, I discuss two additional constraints that aid factorization of musical signals: harmonic and co-occurrence constraints. Harmonic dictionary learning imposes additional harmonic constraints upon the atoms of the learned dictionary while allowing the dictionary size to grow appropriately during the learning procedure. Our proposed method restricts each spectral atom to contain only one musical pitch. When there is significant spectral-temporal overlap among the musical sources, our method outperforms popular existing matrix factorization methods as measured by the recall and precision of learned dictionary atoms. Meanwhile, co-occurrence constraints enforce dependence within predetermined groups of atoms, thereby allowing objects to be represented using multiple atoms instead of only one atom. We introduce three simple and convenient multiplicative update rules for NMF that enforce dependence among atoms. Using examples in music transcription, we demonstrate the ability of these updates to represent each musical note with multiple atoms and cluster the atoms for source separation purposes.

Second, we study how spectral and temporal information extracted by nonnegative factorizations can improve upon musical instrument recognition. Musical instrument recognition has drawn plenty of attention for its ability to facilitate other tasks in music information retrieval such as transcription and search. However, instrument recognition in melodic musical signals remains difficult, especially for classification systems that rely entirely upon spectral information instead of temporal information. Here, we propose a simple and effective method of combining spectral and temporal information for instrument recognition. While existing classification methods use traditional features such as statistical moments, we extract novel features from spectral and temporal atoms generated by nonnegative matrix factorization (NMF) using a biologically motivated multiresolution gamma filterbank. Unlike other methods that require thresholds, safeguards, and hierarchies, the proposed spectral-temporal method requires only simple filtering and a flat classifier. This method is also effective; instrument recognition accuracy in monophonic isolated sounds is 92.3% for twenty-four instrument classes, and accuracy in solo melodic phrases is 96.2% for eleven instrument classes. Using instrument family classifications, accuracy in solo melodic phrases is 97.4% for three instrument families.

Finally, we study how to perform sparse factorization when a large dictionary of musical atoms is already known. Sparse coding methods such as matching pursuit (MP) have been applied to problems in music information retrieval such as transcription and source separation with moderate success. However, when the set of dictionary atoms is large, identification of the best match in the dictionary with the residual is slow -- linear in the size of the dictionary. Here, we propose a variant called approximate matching pursuit (AMP) that is faster than MP while maintaining scalability and accuracy. Unlike MP, AMP uses an approximate nearest-neighbor (ANN) algorithm to find the closest match in a dictionary in sublinear time. One such ANN algorithm, locality-sensitive hashing (LSH), is a probabilistic hash algorithm that places similar, yet not identical, observations into the same bin. We illustrate the effectiveness of AMP by decomposing musical signals with respect to a large dictionary containing over 170,000 spectra of musical sounds. While the accuracy of AMP is comparable to similar MP methods, the computation time is reduced. Also, by using LSH, this method scales easily; the dictionary can be expanded without reorganizing any data structures.

Traditional cooperative communications can greatly improve communication performance. However, transmissions from multiple relay nodes are challenging in practice. Single transmissions using time-division multiple access cause large transmission delay, but simultaneous transmissions from two or more nodes using frequency-division multiple access (FDMA), code-division multiple access (CDMA), or distributed space-time codes are associated with the issues of imperfect frequency and timing synchronization due to the asynchronous nature of cooperation. In this dissertation, we propose a novel concept of wireless network cocast (WNC) and develop its associated space-time network codes (STNCs) to overcome the foretold issues. In WNC networks, each node is allocated a time slot for its transmission and thus the issues of imperfect synchronization are eliminated. To reduce the large transmission delay, each relay node forms a unique signal, a combination of the overheard information, and transmits it to the intended destination. The combining functions at relay nodes forms a STNC that ensures full spatial diversity for the transmitted information as in traditional cooperative communications. Various traditional combining techniques are utilized to design the STNCs, including FDMA-like and CDMA-like techniques and transform-based techniques with the use of Hadamard and Vandermonde matrices. However, a major distinction is that the combination of information from different sources happens within a relay node instead of through the air as in traditional cooperative communications. We consider a general case of multiuser relay wireless networks, where user nodes transmit and receive their information to and from a common base node with the assistance from relay nodes. We then apply the STNCs to multiuser cooperative networks, in which the user nodes are also relay nodes helping each other in their transmission. Since the cooperative nodes are distributed around the network, the node locations can be an important aspect of designing a STNC. Therefore, we propose a location-aware WNC scheme to reduce the aggregate transmit power and achieve even power distribution among the user nodes in the network. WNC networks and its associated STNCs provide spatial diversity to dramatically reduce the required transmit power. However, due to the additional processing power in receiving and retransmitting each other's information, not all nodes and WNC networks result in energy efficiency. Therefore, we first examine the power consumption in WNC networks. We then offer a TDMA-based merge process based on coalitional formation games to orderly and efficiently form cooperative groups in WNC networks. The proposed merge process substantially reduces the network power consumption and improves the network lifetime.

To secure next-generation wireless systems, robust authentication mechanisms are required to mitigate acts of message forgery and the nefarious actions of malicious actors. While cryptographically secure authentication devices have historically been included in upper-layer wireless protocols, these approaches require that nodes impart a significant amount of upper-layer processing to extract and decode the authentication message. Authentication at the physical-layer can prevent wasteful processing of unintended, uninteresting, or maliciously fabricated transmissions, allowing nodes to quickly authenticate legitimate users and implicate charlatans. We propose a fingerprinting method for authenticating wireless systems that exploits typical receiver preprocessing algorithms, such as channel equalization, to ameliorate the distortions of previous "blind superposition" embedding approaches. We consider augmenting current intrinsic channel-based authentication schemes with an! extrinsic, synthetically generated fingerprint signal that is embedded by the transmitter. We consider the heterogeneous wireless broadcast system, consisting of modified (aware) and unmodified (unaware) receivers, while also considering scenarios where channel state information (CSI) is available / unavailable to the transmitter. We present a taxonomy of fingerprinting approaches that operate in the time, frequency, and spacial dimensions, and we discuss how our method can be applied to multiple-input-multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) systems. Finally, we demonstrate how our fingerprinting method can be used in Dynamic Spectrum Access theaters, by establishing edifice for active spectrum sensing. While the focus of this work is on signal fingerprinting for the purpose of transmitting an authentication signal, our embedding approach is not limited to authentication applications.

Multimedia content sharing and distribution over multimedia social networks is more popular now than ever before: we download music from Napster, share our images on Flickr, view user-created video on YouTube, and watch peer-to-peer television using Coolstreaming, PPLive and PPStream. Within these multimedia social networks, users share, exchange, and compete for scarce resources such as multimedia data and bandwidth, and thus influence each other's decision and performance. Therefore, to provide fundamental guidelines for the better system design, it is important to analyze the users' behaviors and interactions in a multimedia social network, i.e., how users interact with and respond to each other. Game theory is a mathematical tool that analyzes the strategic interactions among multiple decision makers. It is ideal and essential for studying, analyzing, and modeling the users' behaviors and interactions. In this thesis, game theory will be used to model users' behaviors in social networks and analyze the corresponding equilibria. Since users in different multimedia social networks may have different types of interdependency, to effectively model the users' behaviors and interactions, we should use different games for different multimedia social networks. In this thesis, we first illustrate how to use game theory to analyze and model users' behaviors in multimedia social networks by discussing the following three scenarios: 1. In the first scenario, we consider a non-cooperative multimedia social network where users in the social network compete for the same resource. We use multiuser rate allocation social network as an example for this scenario. 2. In the second scenario, we consider a cooperative multimedia social network where users in the social network cooperate with each other to obtain the content. We will use cooperative peer-to-peer streaming social network as an example for this scenario. 3. Since users in social networks are rational thus naturally selfish, they will not cooperate with others unless cooperation can improve their own performance. Therefore, cooperation stimulation is an important issue in cooperative social networks. In the third scenario, we consider how to use the indirect reciprocity game to stimulate cooperation among users. Moreover, the concept of ``multimedia social networks" can be applied into the field of signal and image processing. If each pixel/sample is treated as a user, then the whole image/signal can be regarded as a multimedia social network. From such a perspective, we introduce a new paradigm for signal and image processing, and develop generalized and unified frameworks for classical signal and image problems. In this thesis, we use image denoising and image interpolation as examples to illustrate how to use game theory to re-formulate the classical signal and image processing problems.

Utilizing channel reciprocity, the traditional time-reversal technique boosts the signal-to-noise ratio at the receiver with very low transmitter complexity. However, the large delay spread gives rise to severe intersymbol interference (ISI) when the data rate is high, and the performance is further degraded in the multiuser downlink due to the inter-user interference (IUI). With perfect channel state information (CSI), optimum linear waveform design can be calculated to satisfy each user's quality-of-service (QoS) constraint. In practice, however, estimation errors are inevitable and thus the estimated channel is imperfect. Such imperfect CSI can impair the performance severely due to the sub-optimal design. Therefore, in this work, we explored the robust waveform design for the time-reversal multiuser downlink communication system. We formulated an optimization problem with MSE QoS constraints and considered the true channel to be in a set of channels with bounded error from the estimated channel. The optimization problem is further transformed into a standard convex optimization which can be efficiently solved using common optimization packages. Numerical simulation results are shown to demonstrate the proposed robust waveform design can outperform the non-robust one at high SNR.

In this talk, we propose a new protocol that leverages user cooperation to improve the transmission reliability to a common destination. The whole data frame is divided into K time slots, in which all clusters work in a TDMA way. Besides sending local symbols, each node also behaves as a decode-and-forward relay to other clusters. The local symbol and relay symbol are linearly coded by the signature waveforms to avoid inter-user interferences. Transmit beamforming is used within each cluster to guarantee coherent combining at the destination, and the decoding at both the source nodes and destination is based on linear de-correlator. We derived both the exact Symbol Error Rate (SER) for M-ary PSK signal and the asymptotic SER at high SNR regions. We showed that the transmission delay can be reduced dramatically with a linear loss of diversity order. Finally, the simulation results justify the advantage of the proposed protocol.

In this talk I will present a game-theoretical approach to provide a framework for optimal template selection in image prediction. Image prediction is an effective tool for coding still images and intra pictures in video. Template matching algorithms which use neighboring blocks of the prediction target as templates have been widely used for image prediction. The assumption of these approaches is that the template has a similar textural structure as the prediction target. Up to now these approaches all use pre-fixed templates for all prediction target. However, in real images, these fixed templates are very likely to contain textures that are not or are not significant in the prediction target and these insignificant textures introduces larger prediction residues or cause failure of template matching. In this paper, we propose a coalitional game in which every pixel is treated as a player and tries to seek partners to form a coalition to capture the texture structure. By forming a coalition, every player in the coalition can obtain a gain of improving the ability of capturing the texture structure of coalition while incurring a cost of introducing textural variance within the coalition. Experimental results show that the proposed game-theoretical approach outperforms the conventional pre-fixed template matching prediction up to 2dB coding gain.

Cooperative communications, in which single-antennas nodes cooperate to each others such as those in wireless network cocast (WNC), can achieve transmit power saving. However, due to additional processing power in relaying each other information, not all nodes and cooperative network results in energy efficiency. To ensure energy efficiency in WNC networks, we propose a merge process that is based on coalition formation games to form cooperative groups. A node is merged into a cooperative group if the merge leads to power saving for the group and also the individual members. Simulation is provided to corroborate the energy efficient WNC.

A physical-layer fingerprint embedding scheme for orthogonal frequency division multiplexing (OFDM) transmissions using an overlay approach is presented, where the fingerprint signal conveys a low capacity communication suitable for authenticating the transmission and further facilitating secure communications. We improve upon channel-like fingerprinting overlay designs that blindly use past channel state information by leveraging predictive filtering to reduce model mismatch error when recovering the fingerprint signal. The detection performance of a digital fingerprint message in time-varying channel conditions is presented, where CSI used to design the overlay is obtained via Kalman prediction. A fingerprint signal bit error rate improvement of 8-9 dB over designs that do not incorporate prediction is demonstrated through simulation for some channel conditions.

In multinode cooperative communications, simultaneous transmissions from two or more nodes are challenging due to its asynchronous nature. In addition, channel estimation is a costly task due to the amount of training, especially when the number of cooperative users is large. Considering these practical challenges in multinode cooperative communications, we propose a new transmission scheme, namely differential space-time network coding (DSTNC), to overcome the problems of imperfect synchronization and complicated channel estimation. Each user in the network linearly combines the correctly decoded symbols by a network coding vector, which is designed to achieve full diversity without introducing large time delay. The pairwise error probability (PEP) is analyzed and the design criteria of the DSTNC are derived based on the PEP. The proposed DSTNC scheme can be applied to any number of cooperative users. Simulation results are shown to verify the performance of the proposed transmission scheme.

In this talk, we study the image interpolation from the game theoretic perspective and formulate the image interpolation problem as an evolutionary game. In this evolutionary game, the players are the unknown high resolution pixels and the pure strategies of the players are the corresponding low resolution neighbors. By regarding the non-negative weights of the low resolution pixels as the probabilities of selecting the pure strategies, the problem of estimating the high resolution pixels becomes finding the evolutionarily stable strategies for the evolutionary game. Experimental results show that the proposed game theoretical approach can achieve better performance than the state-of-the-art image interpolation methods in terms of both PSNR and visual quality.

Due to the ease with which digital information can be altered, many digital forensic techniques have recently been developed to authenticate multimedia content. One important digital forensic result is that adding or deleting frames from an MPEG video sequence introduces a temporally distributed fingerprint into the video can be used to identify frame deletion or addition. By contrast, very little research exists into anti-forensic operations designed to make digital forgeries undetectable by forensic techniques. In this talk, we propose an anti-forensic technique capable of removing the temporal fingerprint from MPEG videos that have undergone frame addition or deletion. We present experimental results that demonstrate that our proposed anti-forensic technique can effectively remove this fingerprint.

Cognitive radio technology is a new revolutionary communication paradigm which allows flexible access to spectrum resources and leads to efficient spectrum sharing. Recent studies have shown that cognitive radio is a promising approach to improve efficiency of spectrum utilization, because wireless users are capable of accessing the spectrum in an intelligent and adaptive manner. The theory of cognitive radio is however still immature to fully understand its broader impacts on the design of future wireless networks. This dissertation contributes to the advancement of cognitive radio technology by analyzing wireless users' interaction in a network and developing game theoretic frameworks to thwart selfish and malicious behaviors, with the goal to improve system performance by stimulating selfish users and enhance network security against malicious users.

We first develop a cheat-proof repeated spectrum sharing game, which provides the incentive for selfish users to cooperate with each other and reveal their private information truthfully. We propose specific cooperation rules based on the maximum total throughput and proportional fairness criteria, and investigate the impact of spectrum sensing duration on system performance.

We also consider the situation where a group of selfish users collude for higher payoffs. We propose a novel multi-winner spectrum auction framework which did not exist in auction literature, and develop collusion-resistant auction mechanisms to suppress the collusive behaviors. In addition, we apply the semi-definite programming relaxation to significantly reduce the complexity of algorithms.

When malicious users are taken into consideration, we apply game theoretic tools to thwart potential malicious behavior in cognitive radio networks. Specifically, we model the anti-jamming defense as a zero-sum game, and derive the optimal strategy for secondary users to execute in face of jamming threats. Moreover, we propose learning schemes for secondary users to gain knowledge of adversaries.

Finally, we consider security countermeasures against eavesdroppers, and propose a cooperation paradigm that primary users improve secrecy with the help of trustworthy secondary users. We derive the achievable pair of primary users' secrecy rate and secondary users' transmission rate under various circumstances, and model the interaction between primary users and secondary users as a Stackelberg game.

Image interpolation addresses the problem of generating a high-resolution image from its low-resolution version. Edge-directed interpolation schemes, which can adapt to local structures through the assistance of high-resolution image covariance, achieve better visual quality than traditional interpolation schemes. However, these methods usually assume stationarity in pixel values and estimate covariance based on some heuristically determined window, which is not optimal. Motivated by this fact, in this talk, we will discuss the possibility of adaptive estimation of image covariance and its application in image interpolation. Moreover, we demonstrate, by experiment results, the potential performance of this method and illustrate some key issues of applying coalition formation game to this problem.

Content-based search is one of the most central problems in music information retrieval. This type of search uses an audio query, often provided as an acoustic waveform, to retrieve similar pieces of music from a database. Operations such as audio fingerprinting and cover song retrieval have been used to search depending upon the level of similarity desired between the query and the retrieved matches. One type of search -- an acoustic waveform query into a symbolic MIDI database -- has been overlooked. Considering the abundance of MIDI data openly available, this type of search is growing in importance. However, the mapping of acoustic and symbolic data into a common feature space has not been thoroughly investigated for the purpose of search. In this talk, we propose a system that executes an efficient search using approximate nearest-neighbor methods as well as a common feature set that is robust to musical and environmental variations between the acoustic and symbolic domains.

Multi-path effect makes high speed broadband communications a very challenging task due to the severe inter-symbol interference (ISI). By concentrating energy in both the spatial and temporal domains, time-reversal (TR) pre-filtering technique provides a great potential of low-complexity energy-efficient communications. In this paper, we propose to use TR pre-filtering in a multiuser downlink system with large delay spread channels, and develop a new concept of time-reversal division multiplexing (TRDM), in which the location-specific signatures between the base station and users are used to separate intended signals. We investigate the system performance in the cases with one and multiple transmit antennas, and the latter can provide an even better spatial focusing effect. Experimental measurements are shown to verify the spatial and temporal focusing effects in real-life multi-path environments. We also use numerical simulations to justify the theoretical analysis, and the proposed scheme is shown to achieve good performance.

Guest speaker

Utilizing channel reciprocity, the time-reversal (TR) technique boosts the signal-to-noise ratio at the receiver with very low transmitter complexity. However, the large delay spread gives rise to severe intersymbol interference (ISI) when the data rate is high, and the performance is further degraded in the multiuser downlink due to the inter-user interference (IUI). In this work, we study the weighted sum rate optimization problem in the multiuser downlink with ISI using linear precoding. By exploiting the relation between the allocated power and the SINR targets, an iterative algorithm is proposed to jointly optimize the power allocation together with the transmit precoder design. Simulation results are shown to demonstrate the superior performance of the proposed optimization algorithm in comparison with TR and the zero-forcing method.

We present a method for overlaying orthogonal frequency division multiplexing (OFDM) transmissions with a fingerprint message at the physical-layer, where the fingerprint signal conveys a low capacity communication suitable for authenticating the transmission and further facilitating secure communications. A novel approach is discussed where previous channel-state information (CSI) is incorporated into the design of the fingerprint, allowing the signal to mimic distortions typical of time-varying channels. The fingerprint message is only visible to aware receivers who explicitly preform detection of the signal, but is invisible to receivers employing typical channel equalization. A taxonomy of overlay designs is discussed and these designs are explored through experiment using time-varying CSI recorded from an IEEE802.16e Mobile WiMax base-station. The performance of the fingerprint signal as received by a WiMax subscriber is demonstrated using CSI measurements derived from the downlink signal. Detection performance for the digital fingerprint message in time-varying channel conditions is also presented via simulation.

The traditional half-duplex relaying system with coherent modulation is suffering low channel use and increased channel estimation overhead. To effectively overcome these shortcomings, this work focuses on a two-way relaying protocol with non-coherent differential modulation. The bidirectional communications, assisted by a set of K parallel relays, take place in two phases. In the multiple access (MAC) phase, the two sources simultaneously send their differentially encoded BPSK symbols to the relays; while in the broadcast (BC) phase, all relays send through orthogonal channels a differentially encoded symbol that indicates whether the two source symbols have the same signs or not. We designed the optimal maximum a posteriori (MAP) detectors at both the relays and sources. To analyze the error performance, we approximated the MAP detector at the relays as a multi-user detector followed by a network coding encoder. In the case of single relay, we showed that the MAP decoder at the sources is actually equivalent to the standard DBPSK decoder for the relay-to-source channel and thus derived the exact end-to-end decoding error. To minimize the average decoding errors, we also investigated the power allocation problem by use of asymptotic analysis. We showed that the optimal source power is inversely proportional to the square root of the channel gain of the source-to-relay channel, and the optimal relay power decreases with system SNR. For the multiple relay cases, though the exact analysis is unavailable, we developed the upper and lower bounds on system performances and showed that the diversity order is the ceiling of k/2.

Due to the broadcast nature, wireless transmissions can be overheard by any receiver near the destination. A physical layer approach for secure wireless cooperative communications is proposed in this paper. Considering the asynchronous nature of cooperative communications, this paper proposes a weighted space-time network coding (WSTNC) scheme for multinode cooperative communications to prevent eavesdropping and overcome the problem of imperfect synchronization. In the proposed scheme, training symbols are transmitted by the destination (D) instead of the user nodes. Therefore, each user node can obtain the channel state information (CSI) between itself and D, while the eavesdropper (E) can get nothing useful. By exploiting local CSI and the symbols to be transmitted, weighting coefficient is designed for each user node to prevent E from detecting and ensure successful detection at D. Space-time network codes are design to achieve full diversity at D and improve the transmission efficiency for the asynchronous network. The design criteria of the WSTNC is derived based on the security requirement and the pairwise error probability (PEP). Simulation results are presented to verify the performance of the proposed WSTNC scheme.

Time-reversal (TR) is an efficient pre-equalization technique with proven capability of leveraging the channel signature property and collecting multipath gain in large delay spread wireless environment. A large amount of literatures and experiments investigated its performances and temporal-spatial focusing effect in the single user scenario. Yet, little work has been done in exploiting the special focusing effect in the multi-user networks. Motivated by that, in this work, we proposed a TR-based multicasting communication system with highly affordable complexity and worked in hoping of being able to answer the following fundamental questions: Is it possible (or feasible) to do so? What is the SINR achieved at each user on average? How fast can this network communicate? What is the outage performance of this network? In this talk, we would first looked at a system model that reveals the essence of multi-path wireless channels but is still analytically tractable for us to get meaningful results. And then, we shall together evaluate its SiNR level, maximum achievable sum rate, and three different kinds of outage probabilities. Analytical expressions and equations will be presented, but detailed derivation will be skipped in this talk due to limited time. A set of numerical results will also be shown at the end of this talk. A stronger generalization equipped with multiple antennas is currently ongoing and almost done, which will come out shortly but not be included in today’s talk.

Image interpolation addresses the problem of generating a high-resolution image from its low-resolution version. Most existing methods of image interpolation mainly rely on local information, which fail when the local geometry cannot be inferred from the neighboring pixels. Motivated by recent development of non-local methods and game theoretic modeling in image denoising, we propose a new scheme for image interpolation. The basic idea is to first interpolate the missing pixels by a classical algorithm, e.g. bilinear, which can be regarded as noisy observations of true values. Then, based these noisy observations and known pixels, we apply linear adaptive filter to non-locally recover the true values of missing pixels. In this recovery process, the design of the optimal structure of candidate sets is critical, which we solve by coalition formation game. Finally, preliminarily experimental results will be shown and followed by the discussion of the future work.

Cognitive radio technology has been receiving a growing attention in recent years as a revolutionary communication paradigm that can utilize the existing wireless spectrum resources more efficiently. In order to fully utilize spectrum resources, it is very important to design efficient dynamic spectrum access schemes, and one critical prerequisite is precise detection of primary user’s appearance to avoid interference. Various spectrum sensing schemes have been proposed, such as energy detector, feature detector, and matched filter detector. To utilize spatial diversity, multi-user cooperative spectrum sensing is also proposed, which has been shown to achieve better detection accuracy. However, most of the existing cooperative spectrum sensing schemes assume that the secondary users will measure and report the primary user’s presence at the same time, which may actually result in collisions with the primary user. In today’s talk, an asynchronous cooperative spectrum sensing is presented, in which different users sense the licensed spectrum band and fuse their local detection results to the fusion center at different time epochs. The fusion center can adopt an optimal decision combination structure so that the average cost of sensing can be minimized. It is shown that the asynchronous cooperative sensing achieves lower cost than synchronous cooperative sensing.

Cognitive Radio is a promising technology that can alleviate the spectrum shortage problem by enabling unlicensed users equipped with cognitive radios to coexist with incumbent users in licensed spectrum bands while causing no interference to incumbent communications. Spectrum sensing is one of the essential mechanisms of cognitive radios and its operational aspects are being investigated actively. Till now the effort has been made by the secondary users for spectrum sensing. However, the primary user may have the incentives to help the secondary users to improve the security of CRs as well as reduce the interference of primary transmission. In this talk, we will demonstrate the tradeoff of primary user between the degradation of legacy receiver and reduce the false positive of spectrum sensing by applying physical layer fingerprint onto the primary signal.

Although cognitive radio technology improves efficiency of spectrum utilization, usually primary users do not gain directly from opening up the spectrum except spectrum trading. However, if information secrecy is a concern, primary users may benefit from the simultaneous transmission of secondary users. In this talk, we investigate the situation where an eavesdropper attempts to decode a primary user's message, and the primary user improves the secrecy rate with the help of a secondary user. In particular, we derive the pair of the primary user's secrecy rate and the secondary user's transmission rate under various circumstances, and further model this scenario as a game where both users decide how much power to use. The Nash equilibrium of this game is analyzed, and simulation results are presented to verify the performance.

How to adaptively choose optimal neighborhoods is very important to pixel-domain image denoising algorithms since too many neighborhoods may cause over-smooth artifacts and too few neighborhoods may not be able to efficiently remove the noise. While the Stein’s principle is shown to be able to estimate the true mean square error (MSE) for determining the optimal neighborhoods, there exists a trade-off between the accuracy of the estimate and the minimum of the true MSE. In this paper, we study the impact of this trade-off and formulate the image denoising problem as a coalition formation game. In the game, every pixel is treated as a player, who tries to seek partners to form a coalition to achieve better denoising results. By forming a coalition, every player in the coalition can obtain a gain of improving the accuracy of the Stein’s estimate while incurring a cost of increasing the minimum of the true MSE. Moreover, we propose a heuristically distributed approach for coalition formation. We also show that the traditional approaches that use a heuristically determined candidate set are special cases of the game theoretical framework by choosing the utility function without a cost term. Finally, experimental results show that the proposed game theoretical approach can achieve better performance than the nonlocal method in terms of both PSNR and visual quality.

Music information retrieval is hard -- often too hard to perform without making some assumptions. If we design solutions that cover the entire space of acoustic possibilities, which researchers often do, we may design a system that is either inaccurate or prohibitively slow. One way to impose meaningful assumptions is through side information: relevant information that eases the task of processing a particular input. Simply put, side information makes many unsolvable tasks in music information retrieval solvable. But how do we find this side information? One valuable source is the MIDI file. Thankfully, there are millions of MIDI files all over the Internet waiting to be harvested. However, finding the correct side information for a given input is not straightforward. In this talk, we propose the idea of a "cross-layer search" -- in this case, finding a MIDI file that relates to a given musical waveform. By performing a content-based search on a large MIDI database, we can efficiently find side information for MP3 or WAV files and therefore improve the performance of subsequent MIR systems.

Objective image quality metric plays a critical role in many image processing applications. The most widely used quantity, mean square error (MSE), however, has been shown to be not able to fully predict human perception of image fidelity and quality. Recently, the structural similarity (SSIM) index which captures the structural change between images has been proposed and proved to be effective. Theoretical comparisons between MSE and SSIM motivate us to calculate SSIM using structural similar pixels instead of involving all pixels within a pre-defined block heuristically. We then formulate the image quality assessment problem as a coalition formation game. In this game, each pixel is treated as a player who seeks partners to form a coalition to achieve better assessment. By forming a coalition, every player in the coalition can obtain a gain of reducing the variance of the estimate while incurring a cost of increasing the bias. Finally, preliminarily experimental results will be shown and followed by the discussion of the future work.

Time reversal precoding maximizes the signal-to-noise ratio (SNR) by matched filtering the multipath channel. However, it results in severe temporal sidelobes which cause the inter-symbol-interference (ISI) and thus error floor at high SNR. The intimate connection between multipath and multiple antennas enable us to formulate the multipath channel filter design as a multiple-input multiple-output (MIMO) beamformer design problem. Several different criteria are considered. We show that Minimum mean square error (MMSE) and maximum signal-to-interference-and-noise ratio (MSINR) precoding filters mitigate the ISI while minimizing the degradation of SNR. Simulation results are presented to illustrate the performance improvement.

This talk presents what ideas we have in mind about TimeReversal-based multicasting. It is necessay to point out that this is not yet a complete work. Instead, it investigates the possibilities of applying Time-reversal to multicast application and things beyond. This presentation will be highly conceptual, but tackle some critical issues in TR-based multicasting networks that allow the system to go from theory to reality. In this talk, some basic observations for multicasting will be discussed, which motivate the proposed TR-based multicast system. Also, a effective family of waveform is proposed to mitigate inter-user interference and enhance physical-layer security. Some claims are made togeher with supporting simulation results.

The future communication systems will have to accommodate larger data rates, the natural solution consisting of increasing the bandwidth brings a number of open challenges. In this matter, time reversal (TR) could play a role in the design of the broadband wireless communications. In TR, the time reversed version of the channel impulse response (CIR) is used to precode the transmitted symbols. These time reversed waves propagate in the channel, retrace their former paths and eventually lead to a focus of power in space and time at the receiver. Despite that the channel energy is focused in time and space, the TR system cannot erase inter-symbolinterference (ISI) completely. In this work we examine the effect of ISI by comparing the average energy of ISI and symbol. We derive the exact expressions for the first- and second-order moments of ISI and symbol for TR transmission using the simplified SV channel model. The upper-bound of average ISI to signal ratio is given for SV model. The analytical results can be used to investigate the effects of channel parameters and signal interval on the average ISI to signal ratio.

A framework for introducing an extrinsic fingerprint signal to space-time coded transmissions at the physical-layer is presented, whereby the fingerprint signal conveys a low capacity digital communication suitable for authenticating the transmission and further facilitating secure communications. A novel approach is discussed where the fingerprint signal mimics distortions similar to time-varying channel effects. Specifically, the fingerprint signal is only visible to aware receivers considering previous channel state information and is otherwise invisible to a receiver equalizing according to current channel state information. An augmented signal is created consisting of the original transmission, or primary message, and the fingerprint message. Two example fingerprint signals and detection rules are presented based on pulse-amplitude keying and phase-shift keying approaches. The methods for obtaining the real (intrinsic) channel estimate, the extrinsic fingerprint message, and the primary transmission are analytically demonstrated using general pilot embedding schemes. The worst-case distortions caused by non-ideal equalization of a fingerprinted message are derived using the 2x2 Alamouti code. Simulation results including bit error rate (BER) and model mismatch error using a maximum-likelihood (ML) receiver are presented for both the primary and fingerprint signal, while authentication signal BERs lower than the primary signal are demonstrated.

Mobile phones are among the most popular consumer devices and the recent developments of 3G networks and smart phones enable users to watch video programs by subscribing data plans from service providers. Due to the ubiquity of mobile phones and phone-to-phone communication technologies, subscribers can redistribute the video content to non-subscribers. Such a redistribution mechanism is a potential competitor for the service provider and is very difficult to trace given the users' high mobility. The service provider has to set a reasonable price for the data plan to prevent such re-distribution behavior to protect his/her own profit. In this paper, we analyze the optimal price setting for the service provider by investigating the equilibrium between the subscribers and the secondary buyers in the content-redistribution network. We model the behavior between the subscribers and the secondary buyers as a seller-buyer game and find the optimal price and quantity for both groups of users. We use the optimal price of the redistribution networks to determine the price of the content that can either prevent the redistribution or optimize the content owner's utility. Such an analysis can help the service provider preserve their profit under the threat of the redistribution networks and can improve the quality of service for end users.

How to adaptively choose optimal neighborhoods is very important to pixel-domain image denoising algorithms since too many neighborhoods may cause over-smooth artifacts and too few neighborhoods may not be able to efficiently remove the noise. While the Stein's principle is shown to be able to estimate the true mean square error (MSE) for determining the optimal neighborhoods, there exists a trade-off between the accuracy of the estimate and the minimum of the true MSE. In this paper, we study the impact of this trade-off and formulate the image denoising problem as a coalition formation game. In the game, every pixel is treated as a player, who tries to seek partners to form a coalition to achieve better denoising results. By forming a coalition, every player in the coalition can obtain a gain of improving the accuracy of the Stein's estimate while incurring a cost of increasing the minimum of the true MSE. Finally, experimental results show that the proposed game theoretical approach can achieve better performance than the nonlocal method in terms of both PSNR and visual quality.

The widespread availability of photo editing software has made it easy to create visually convincing digital image forgeries. To address this problem, there has been much recent work in the field of digital image forensics. There has been little work, however, in the field of anti-forensics, which seeks to develop a set of techniques designed to fool current forensic methodologies. In this work, we present a technique for disguising an image’s JPEG compression history. An image’s JPEG compression history can be used to provide evidence of image manipulation, supply information about the camera used to generate an image, and identify forged regions within an image. We show how the proper addition of noise to an image’s discrete cosine transform coefficients can sufficiently remove quantization artifacts which act as indicators of JPEG compression while introducing an acceptable level of distortion. Simulation results are provided to verify the efficacy of this anti-forensic technique.

Due to the ease with which convincing digital image forgeries can be created, a need has arisen for digital forensic techniques capable of detecting image manipulation. Once image alterations have been identified, the next logical forensic task is to recover as much information as possible about the unaltered version of image and the operation used to modify it. Previous work has dealt with the forensic detection of contrast enhancement in digital images. In this paper we propose an iterative algorithm to jointly estimate any arbitrary contrast enhancement mapping used to modify an image as well as the pixel value histogram of the image before contrast enhancement. To do this, we use a probabilistic model of an image’s pixel value histogram to determine which histogram entries are most likely to correspond to contrast enhancement artifacts. Experimental results are presented to demonstrate the effectiveness of our proposed method.

Traditional communication techniques may not perform well under a severe multi-path channel. A novel method is the so-called time reversal, which essentially implements a matched filter without complicated structures. The transmitter uses the time-reversed channel response as a basic waveform, and the energy will be automatically focused at the receiver. In this talk, we will give a general overview of the time-reversal architecture, both the theoretic background and practical issues related to the project. Details of software simulation and hardware implementation are discussed, and simulation results are presented to gain an insight of this novel approach.

In this paper, we investigate the security mechanism when secondary users are facing the jamming attack, and propose a stochastic game framework for anti-jamming defense. At each stage of the game, secondary users observe the spectrum availability, the channel quality, and the attackers?strategy from the status of jammed channels. According to this observation, they will decide how many channels they should reserve for transmitting control and data messages and how to switch between the different channels. Using the minimax-Q learning, secondary users can gradually learn the optimal policy, which maximizes the expected sum of discounted payoffs defined as the spectrum-efficient throughput. The proposed stationary policy in the anti-jamming game is shown to achieve much better performance than the policy obtained from myopic learning, which only maximizes each stage’s payoff, and a random defense strategy, since it successfully accommodates the environment dynamics and the strategic behavior of the cognitive attackers.

Traditional cooperative communications can improve communication reliability. However, transmissions from multiple relay nodes are challenging in practice. Single transmissions in TDMA manner cause large transmission delay, but simultaneous transmissions from two or more nodes are associated with the issue of imperfect frequency and timing synchronization. In this talk, following the novel concept of wireless network cocast (WNC) presented previously, transform-based coding is utilized to design space-time network codes for a group a N client nodes that cooperate to one another in their transmissions to a common base node. Each client node also acts as a relay to form a unique linearly-coded signal from the overheard symbols of other source nodes and transmit it to the base node in its dedicated time slot. Based on the pair-wise error probability (PEP), the code matrix is designed to achieve full diversity for all transmitted symbols.

Instrument recognition has drawn plenty of attention for its ability to facilitate other tasks in music information retrieval such as transcription and search. This classification problem has been adequately solved for monophonic musical signals but not for polyphonic signals. Furthermore, most classification systems rely entirely upon spectral information instead of temporal information. In this work, we test the hypothesis that temporal information can improve upon the accuracy achievable by the state of the art in polyphonic musical instrument recognition. Unlike existing temporal classification methods which use traditional features such as temporal moments, we extract novel features from temporal atoms generated by nonnegative matrix factorization (NMF) in a biologically motivated manner. We show that this proposed feature, the multiresolution gamma filterbank response (MGFR), can differentiate among certain families of instruments, and when combined with spectral information, can improve classification performance even further.

Musical instrument recognition has recently benefited from advancements in dictionary learning. Because musical signals contain acoustic events that often reoccur over many time units, the data in a musical signal is highly redundant. There already exist dictionary-learning methods that exploit the spectral redundancy among sounds in a musical signal. Many of these methods depend upon nonnegative matrix factorization (NMF) to obtain low-rank approximations of audio spectrograms of the signal. While these methods are effective in removing spectral redundancy from the signal, redundancy remains in the temporal domain. The temporal activities of factorized atoms usually resemble known patterns, particularly in musical signals. In this presentation, we propose a method for classifying musical signals that exploits these common patterns of temporal activity. From each atom, we extract a set of temporal envelope parameters which quantify the attack rate, decay rate, and energy modulation of the temporal envelope. When combined with spectral features, these parameters improve classification performance over methods which only rely on spectral information.

In cognitive networks, since nodes generally belong to different authorities and pursue different goals, they will not cooperate with others unless cooperation can improve their own performance. Thus, how to stimulate cooperation among nodes in cognitive networks is very important. However, most of existing game-theoretic cooperation stimulation approaches rely on the assumption that the interactions between any pair of players are long-lasting. When this assumption is not true, according to the well-known Prisoner's Dilemma and the backward induction principle, the unique Nash equilibrium (NE) is to always play non-cooperatively. In this paper, we propose a cooperation stimulation scheme for the scenario where the number of interactions between any pair of players are finite. The proposed algorithm is based on indirect reciprocity game modelling where the key concept is "I help you not because you have helped me but because you have helped others". We formulate the problem of finding the optimal action rule as a Markov Decision Process (MDP) and propose a modified value iteration algorithm to find the optimal action rule. Using the packet forwarding game as an example, we show that with an appropriate cost-to-gain ratio, the strategy that forwarding $i$ packets to the receiver with reputation level i is an evolutionarily stable strategy (ESS). Finally, simulations are shown to verify the efficiency and effectiveness of the proposed algorithm.

Much research in cooperative communications has focus on simultaneous transmissions from different relay nodes with an assumption of perfect timing and frequency synchronization and perfect channel information at the receivers, which is challenging to be met in practical transmissions. Recent work have investigated the design of distributed space-time code to overcome the issue of imperfect timing or/and frequency synchronization. Exact channel state information is required at all the receivers in these schemes. However, channel estimation is known to be a challenging and costly task especially in multi-antenna or multi-node wireless systems since the amount of training or convergence time (incurred by blind techniques) grows with the number of links. It’s imperative to develop differential techniques for multi-node cooperative communications since their burden of channel estimation is even more severe than multi-antenna systems. In this talk, a differential space-time network coding scheme will be introduced, based on space-time network code(STNC) proposed by Lai et al.. The new coding scheme can overcome the synchronization and channel estimation problems, and it differs from STNC in two aspects: differential encoding and method of network coding.

In this work, we aim to solve the multiuser multi-input multi-output (MIMO) downlink beamforming problem where one multi-antenna base station broadcasts data to many users. Each user is assigned multiple data streams and has multiple antennas at its receiver. The data streams for each user are subject to an average signal-to-interference-plus-noise-ratio (SINR) constraint. Efficient solutions to the joint transmit-receive beamforming and power allocation problems based on iterative methods are proposed. The adopted beamforming method is a maximum SINR filter bank which exploits cooperation between the data streams of a user. Based on this filter bank, we derive an SINR balancing property which simplifies the complex power allocation problem to a linear one. Simulation results verify the superiority of the proposed algorithms over previous works with approximately the same complexity.

Very recently, an energy spreading transform (EST) based iterative detection scheme was proposed to multiple-input-and-multiple-output (MIMO) fading channels, ending up with an EST-based MIMO system. The EST spreads the energy of each symbol over the entire symbol block, providing diversity and enhancing the detection reliability at the receiver. Most of existing analyses on this EST-based MIMO system mainly focus on its bit-error-rate (BER) performance. However, more fundamental aspects such as capacity has not been well investigated. In this talk, I shall first show our evaluation on the contribution of the EST-based iterative processing to the system capacity. And then I would present the optimal trade-off between diversity and multiplexing of this EST-based MIMO system. Some counterintuitive results will be shown for further discussion in hoping to solicit some helpful suggestions from you.

Traditional cooperative communications consider dedicated relays, while often such relays may not be available. We consider wireless transceivers that cooperatively relay signals in addition to their own primary communication missions. Under the best-effort delivery policy, a node is not obligated to devote energy for relaying signals, nor does it provide a guarantee of signal quality to retransmissions. Instead the relay sacrifices energy at its own discretion with priority given to the primary communication mission. We consider one best-effort delivery problem: a system that helps transmit an additional signal within its original transmission energy budget while inducing minimal degradation to the primary signal. To maintain this constraint, we consider the feasibility of reallocating energy from pilot signals used for channel estimation toward the relaying service, as channel conditions become stationary. We demonstrate that transmitter energy may be strategically allocated between a relay component and a pilot component of the transmission using best-effort delivery, and that this allocation may dynamically change in response to changing channel conditions and/or QoS requirements. We present the dynamic power allocation problem using generalized pilot-embedding methods, to demonstrate the possibility of best-effort transmission with minimal degradation to primary transmissions. Optimal power allocation rules with respect to primary-user are discussed.

Cognitive radio technologies have become a promising approach to increase the efficiency of spectrum utilization. Although cognitive radio has been intensively studied in recent years, only a few works have discussed security aspects. In this talk, we focus on the jamming attack, one of major threats to cognitive radio networks, where several malicious attackers want to jam the secondary user's communication link by injecting interference. We model this scenario into a jamming game, in which the optimal strategy can be derived using the Markov decision process approach. Furthermore, learning schemes are proposed for the secondary user to learn the wireless environment, such as the primary users' access pattern and the number of attackers. Finally, simulation results are presented to verify the performance.

Due to the ease with which convincing digital image forgeries can be created, a need has arisen for digital forensic techniques capable of detecting image manipulation. Once image alterations have been identified, the next logical forensic task is to recover as much information as possible about the unaltered version of image and the operation used to modify it. Previous work has dealt with the forensic detection of contrast enhancement in digital images. In this talk we propose an iterative algorithm to jointly estimate any arbitrary contrast enhancement mapping used to modify an image as well as the pixel value histogram of the image before contrast enhancement. To do this, we use a probabilistic model of an image’s pixel value histogram to determine which histogram entries are most likely to correspond to contrast enhancement artifacts. Experimental results are presented to demonstrate the effectiveness of our proposed method.

Users watching live streaming in the same wireless network share the same limited bandwidth of backbone connection to the Internet, thus they might want to cooperate with each other to obtain better video quality. These users form a wireless live-streaming social network. Every user wishes to watch video with high quality while paying as little as possible cost to help others. This paper focuses on providing incentives for user cooperation. We propose a game-theoretic framework to model user behavior and to analyze the optimal strategies for user cooperation simulation in wireless live streaming. We first analyze the Pareto optimality and the time-sensitive bargaining equilibrium of the two-person game. We then extend the solution to the multiuser scenario. We also consider potential selfish users?cheating behavior and malicious users?attacking behavior and analyze the performance of the proposed strategies with the existence of cheating users and malicious attackers. Both our analytical and simulation results show that the proposed strategies can effectively stimulate user cooperation, achieve cheat free and attack resistance, and help provide reliable services for wireless live streaming applications.

Cognitive radio is an emerging communication paradigm in recent years that has received an increasingly growing attention, since it can utilize the limited spectrum resources in a more intelligent and flexible way. Since the radio spectrum environment is dynamic in nature, due to primary users?activity, a lot of stochastic modeling approaches, such as those based on Markov chain and Markov Decision Process (MDP) modeling, have been proposed so as to predict future traffic patterns. As various secondary users compete for the spectrum resources, non-cooperative games are also considered to model the intelligent interactions among secondary users. However, few of these works have considered the existence of malicious users who will launch harmful attacks to a secondary user network, and provide a quantitative analysis of their potential damage. In today’s presentation, I will talk about one prevailing attack in wireless networks, jamming attack, and analyze its impact on a! cognitive radio network. I will first formulate the anti-jamming defense of the secondary users against malicious users as a (zero-sum) game. Considering the dynamic spectrum opportunities, I extend the static game to a stochastic game, where the secondary users and malicious users?actions together with the primary users?activities determine the state transitions. Then, I derive the optimal policy for both players using minimax-Q learning, which only requires each player’s own local information for updating strategies. Finally, the optimal policy for a simple cognitive radio network setting is demonstrated through simulations, followed by conclusions and future work.

Music source separation has drawn plenty of attention for its ability to facilitate tasks in music information retrieval. However, source separation is difficult because there does not exist a unique solution; given a musical mixture, there are several valid ways to decompose the mixture into its individual sources. In this work, we have proposed a novel use of co-occurrence constraints to improve the performance of nonnegative matrix factorization (NMF) ?a popular, convenient, and effective method for decomposing spectrograms. We have developed three new multiplicative update rules to influence the amount of dependence among musical atoms. Here, we demonstrate the ability of these updates to learn more accurate representations of musical objects using multiple atoms. We have also proposed a novel method that imposes additional harmonic constraints upon the musical atoms learned by NMF. When there is significant spectral-temporal overlap among the musical sources, our learning method has better recall and precision than other popular existing matrix factorization methods.

While P2P video streaming systems have achieved promising results, they introduce a large number of unnecessary traverse links, which consequently leads to substantial network inefficiency. To address this problem and achieve better streaming performance, we propose to enable cooperation among "group peers", which are geographically neighboring peers with large intra-group upload and download bandwidths. Considering the peers' selfish nature, we formulate the cooperative streaming problem as an evolutionary game and derive the evolutionarily stable strategy (ESS) for every peer. Moreover, we propose a simple and distributed learning algorithm for the peers to converge to the ESSs. With the proposed algorithm, each peer decides whether to be an agent who downloads data from the peers outside the group or a free-rider who downloads data from the agents by simply tossing a coin, where the probability of being a head for the coin is learned from the peer's own past payoff history. Simulation results show that the strategy of a peer converges to the ESS. Compared to the traditional non-cooperative P2P schemes, the proposed cooperative scheme achieves much better performance in terms of social welfare, probability of real-time streaming, and video quality (source rate).

In recent years, a number of image forensic algorithms have been proposed which rely on detecting JPEG compression artifacts. These algorithms are capable of providing evidence of image manipulations, supplying information about an image’s source, and identifying forged regions within an image. None of these algorithms, however, consider the possibility of an image forger using anti-forensic signal processing operations. In this work, we present an anti-forensic technique for disguising an image's JPEG compression history. We show how the proper addition of noise to an image's discrete cosine transform coefficients can sufficiently remove quantization artifacts which act as indicators of JPEG compression while introducing an acceptable level of distortion. Furthermore, we present a method which removes blocking artifacts while preserving the forensically significant properties of an image’s DCT coefficient distribution. Simulation results are provided to verify the efficacy of this anti-forensic technique.

Music source separation has drawn plenty of attention for its ability to facilitate other tasks in music information retrieval. However, source separation is difficult because there does not exist a unique solution; given a mixture, there are several valid ways to decompose the mixture into component sources. Researchers have devoted years of effort toward solving the fully automatic blind source separation problem. Although significant progress has been made along the theoretical and algorithmic aspects of source separation, the separation performance achievable by the state of the art is still not adequate for widespread commercial use. This inadequacy exists in large part because of the prohibitively difficult nature of solving the blind source separation problem. In this talk, we propose a novel method for performing music source separation of a music signal given side information in MIDI format of a similar performance. Our method uses nonnegative matrix factorization -- a popular, convenient, and effective method for decomposing matrices. By exploiting the information that MIDI provides, our method is able to separate sources within highly polyphonic musical mixtures as well as sources which share a significant amount of temporal or spectral overlap.

In cooperative communications different network nodes share their antennas and resources to form a virtual antenna array and improver their performance through spatial diversity. This thesis contributes to the advancement of cooperative communications by developing and analyzing new multiple access cooperation protocols that leverage the benefits of cooperation to upper network layers.

For speech communications networks, we propose a cooperative multiple access protocol that exploits inherent characteristics of speech signals, namely, long periods of silence, to enable cooperation without incurring bandwidth efficiency losses. Using analytical and simulation results we show that the proposed protocol achieves significant increase in network throughput, reduction in delay, and improved perceptual speech quality.

In TDMA networks, we investigate the problem of sharing idle time slots between a group of cooperative cognitive relays helping primary users, and a group of cognitive secondary users. Analytical results reveal that, despite the apparent competition between relays and secondary users, and even in case of mutual interference between the two groups, both primary and secondary users will significantly benefit in terms of maximum stable throughput from the presence of relays.

For random access networks, we find a solution to the problem of achieving cooperation gains without suffering from increased collision probability due to relay transmissions. A novel cooperation protocol is developed and analyzed for that purpose. Analytical and simulation results reveal significant improvements in terms of throughput and delay performance of the network. Moreover, a decrease in collision probability.

Finally, in the framework of a cognitive radio network, we study the negative effects of spectrum sensing errors on the performance of both primary and secondary networks. To alleviate those negative effects, we propose a novel joint design of the spectrum sensing and channel access mechanisms. Results show significant performance improvement in the maximum stable throughput region of both networks.

Within the past decades, the explosive combination of multimedia signal processing, communications and networking technologies has facilitated the sharing of digital multimedia data and enabled pervasive digital media distribution over all kinds of networks. People involved in the sharing and distribution of multimedia contents form multimedia social networks in which users share and exchange multimedia content, as well as other resources. Users in a multimedia social network have different objectives and influence each other's decision and performance. It is of ample importance to understand how users interact with and respond to each other and analyze the impact of human factors on multimedia systems. This thesis illustrates various aspects of issues and problems in multimedia social networks via two case studies of human behavior in multimedia fingerprinting and peer-to-peer live streaming.

Since media security and content protection is a major issue in current multimedia systems, this thesis first studies the user dynamics of multimedia fingerprinting social networks. Before a collusion being successfully mounted, the colluders must be stimulated to cooperate with each other and all colluders have to agree on the attack strategy. Therefore, not all types of collusion are possible. We reduce the possible collusion set by analyzing the incentives and bargaining behavior among colluders. Furthermore, we investigate the side information which improves the traitor-tracing performance and provide the optimal strategies for both users (fingerprint detector and the colluders) in the multimedia fingerprinting social network. We show that the optimal strategies designed based on human behavior can provide more information to the fingerprint detector and effectively improve the collusion resistance.

The second part of this thesis focuses on understanding modelling and analyzing user dynamics for users in various types of peer-to-peer live streaming social networks. We stimulate user cooperation by designing the optimal, cheat-proof, and attack-resistant strategies for peer-to-peer live streaming social networks over Internet as well as wireless networks. Also, as more and more smart-phone users subscribe to the live-streaming service, a reasonable market price has to be set to prevent the users from reselling the live video. We start from analyzing the equilibrium between the users who want to resell the video and the potential buyers to provide the optimal price for the content owner.

Cognitive radio technologies have become a promising approach to efficiently utilize the spectrum. Although many works have been proposed recently in the area of cognitive radio, little effort has been made in content-aware multimedia application over cognitive radio network. In this paper, we study the multimedia streaming problem over cognitive radio network, where there is one primary user and N secondary users. In this problem, the objective of the primary user is to maximize his/her revenue by choosing either to utilize the spectrum himself/herself or to sell the spectrum to the secondary users, while the objective of each secondary user is to maximize his/her payoff by competing with the primary user and other secondary users to buy the spectrum. We formulate the spectrum allocation problem as an auction game and propose to solve the problem using alternative ascending clock auction. We show that the proposed algorithm is cheat-proof and converges to the NE that maximizes social warfare in a finite number of clocks. We prove and demonstrate with simulation results that compared with traditional dual-based optimization algorithm that maximizes social warfare, the proposed method has the cheat-proof property, while compared with second-price sealed-bid auction that has cheat-proof property, the proposed algorithm can achieve much higher social warfare.

In cognitive radio networks, secondary users must sense the primary spectrum bands and only utilize those free spectrum bands where no primary users are present. In order to sufficiently protect the primary user's transmission, the spectrum sensing can take up to 10%~15% of a time slot at low SNRs. In this work, we assume sensing energy constraints on secondary user, i.e. the secondary users can only sense the spectrum for a limited time. We propose to dynamically allocate the spectrum sensing duration to improve the secondary user's payoff functions based on the primary user state. We first discuss the problem under ideal assumption where secondary users have primary user state available at the end of every slot, and then we propose algorithm without this assumption. Simulation results show that our algorithm can improve the secondary user payoff functions by 5%~15%, depending on the assumption we used.

The widespread availability of photo editing software has made it easy to create visually convincing digital image forgeries. To address this problem, there has been much recent work in the field of digital image forensics. There has been little work, however, in the field of anti-forensics, which seeks to develop a set of techniques designed to fool current forensic methodologies. In this work, we present a technique for disguising an image's JPEG compression history. An image's compression history can be used to provide evidence of image manipulation, supply information about the camera used to generate an image, and identify forged regions within an image. We show how the proper addition of noise to an image's discrete cosine transform coefficients can sufficiently remove quantization artifacts which act as indicators of JPEG compression while introducing an acceptable level of distortion. Simulation results are provided to verify the efficacy of this anti-forensic technique.

Cognitive radio technologies have become a promising approach to increase the efficiency of spectrum utilization. Although cognitive radio has been intensively studied in recent years, only a few works have discussed security aspects. In this paper, we focus on the jamming attack, one of major threats to cognitive radio networks, where a malicious user wants to jam the communications of secondary users by injecting interference. Aware of the absence of several primary users and the presence of a malicious user, a secondary user can allocate power to those fallow bands with a randomized strategy, in hope of alleviating the damage caused by the malicious user. We model this scenario into a two-player zero-sum game, and derive its unique Nash Equilibrium under certain conditions using the Colonel Blotto game approach, which provides a minimax strategy that the secondary user should adopt in order to minimize the worst-case damage caused by the malicious user. Simulation results are presented to verify the performance.

In this work our goal is to answer the questions of how to enable cooperative communications in random access networks? And, since cooperation introduces extra transmissions in the channel, what are the benefits and possible tradeoffs associated with cooperation? To achieve this goal, we first propose a cooperation protocol that enables relays to exploit part of the channel resources to offer diversity. Next, a Markov model that characterizes the interaction between relays and different network nodes is developed to investigate the effect of sharing the channel resources between network nodes and relays on the throughput and collision probability. Analytical and numerical results reveal significant performance increase by the virtue of our cooperative protocol.

In cooperative communication protocols, multiple terminals cooperate together forming a virtual antenna array to improve their performance. This thesis contributes to the advancement of cooperative communications by proposing new relay deployment and selection protocols across the network layers that can increase the bandwidth efficiency, reduce the end-to-end transmission power needed to achieve a desired network throughput, maximize the lifetime of a given network, rebuild a disconnected network, and mitigate the effect of channel estimation error and co-channel interference (CCI) problems.

Conventional cooperative schemes achieve full diversity order with low bandwidth efficiency. In this thesis we propose a relay selection cooperative protocol, which achieves higher bandwidth efficiency while guaranteeing full diversity order. We provide answers to two main questions, namely, "When to cooperate?" and "Whom to cooperate with?". Moreover, we obtain optimal power allocation and present the tradeoff between the achievable bandwidth efficiency and the corresponding symbol error rate performance.

We illustrate that the cooperation gains can be leveraged to the network layer. In particular, we propose a cooperation-based routing algorithm, namely, the Minimum Power Cooperative Routing (MPCR) algorithm, which optimally selects relays while constructing the minimum-power route. Moreover, the MPCR can be implemented in a distributed manner. Using analytical and simulation results, we show that the MPCR algorithm achieves significant power savings compared to the current cooperation-based routing algorithms.

We also consider maximizing the network lifetime in sensor networks via deployment of relays. First, we propose a network maintenance algorithm that obtains the best locations for a given set of relays. Second we propose a routing algorithm, namely, Weighted Minimum Power Routing algorithm, that significantly increases the network lifetime due to the efficient utilization of the deployed relays. Finally, we propose an iterative network repair algorithm that finds the minimum number of relays along with their best locations, needed to reconnect a disconnected network.

We complete this thesis by investigating the impact of cooperative communications on mitigating the effect of channel estimation error and CCI. We show that cooperative transmission schemes are less susceptible to the effect of channel estimation error or CCI compared to the direct transmission. Finally we study the tradeoff between the timing synchronization error, emerging in the case of having simultaneous transmissions of the cooperating relays, and the channel estimation error, and show their net impact on the system performance.

Users in multimedia social networks actively interact with each other. It is crucial to study the complex user dynamics and analyze its impact on the performance of multimedia social networks. This paper provides a case study of user dynamics in multiuser collusion attacks against multimedia fingerprinting. During collusion, a group of attackers collectively and effectively attack multimedia fingerprinting system and use multimedia content illegally. We present a game-theoretic framework to model the complex dynamics among colluders, analyze when attackers cooperate with each other, and investigate how a colluder selects his/her fellow attackers to maximize his/her own payoff. Our framework considers both the colluders?risk of being detected by the digital rights enforcer and the reward received from illegal usage of multimedia content. Our analysis shows that colluding with more attackers does not always increase an attacker’s utility, and attackers may not always want to cooperate with each other. We first examine the necessary conditions for attackers to collude together, and study how they select the collusion parameters such that cooperation benefits all colluders. We further study the bargaining process and the fairness solutions for collusion including the time-sensitiveness of multimedia contents. We then study how the number of colluders affects each attacker’s utility, and investigate the optimum strategy that an attacker should use to select fellow attackers in order to maximize his or her own payoff.

Music source separation, an important task in the area of music information retrieval (MIR), has received plenty of attention in the past few years for its potential to improve the performance of other MIR-related tasks. While related to other generic problems in blind source separation, the musical context of this problem contains additional challenges which diminishes the separating power of common solutions, such as independent component analysis (ICA). At the same time, the musical context also contains additional cues which can improve separation performance if exploited properly. In this work, we investigate matrix factorization methods, particularly the nonnegative singular value decomposition (NNSVD), to factorize a time-frequency representation of a musical mixture into its component source signals. Furthermore, we offer a novel contribution to the NNSVD learning process which further exploits the harmonic nature of the input music signal. We demonstrate the effectiveness of this approach through the separation of synthetic and natural music signals, and we compare the approach against other traditional matrix factorization methods.

Cooperative communications have been proposed to exploit spatial diversity gains. In this paper, binary hypothesis distributed detection problem in wireless sensor networks with cognitive-cooperative relay deployment is considered. In energy-constrained networks such as wireless sensor networks, the advantages of cooperation can be further exploited by cognitively utilizing wasted channel/time slots among sensor nodes for optimal data gathering and detection. Wireless sensor networks are also characterized by correlated observations and sending all observations directly to the fusion center all the time is a waste of network-resources. By employing cognitive cooperative relays significant detection performance gains and energy savings can be achieved. A simple example of a binary hypothesis distributed detection problem in a spatio-temporally correlated sensor network with two sensor nodes and a relay node illustrates the significant energy savings achieved through cognitive-cooperation.

Wireless spectrum is a very precious resource. However, a large portion of the assigned spectrum is used sporadically. The limited spectrum resources and the inefficient spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically, i.e., dynamic spectrum access and cognitive radio networks. With cognitive radio technology, future wireless devices are envisioned to be able to utilize the spectrum in a dynamic manner. However, in de-centralized cognitive radio networks, selfish users only aim at maximizing their own benefits. In addition, they are sometimes uncertain about the surrounding environments, such as who else are in the network and what the others do. Thus, it is very important to analyze users?intelligent cooperation and competition behavior from a game-theoretic perspective, as game theory is a well-developed mathematical tool that studies the strategic interactions among rational decision makers under uncertainty. My talk today focuses on how to solve dynamic spectrum allocation problems using game-theoretic approaches. The first part is on relay selection and power control using Stackelberg game, and the second part is about collaboration strategy in cooperative spectrum sensing using evolutionary game modeling.

Recently cognitive radio has attracted intense research interests as an enabling technology for dynamic spectrum access. The research on cognitive radio involves interdisciplinary effort from various technical aspects, including signal processing, communications, cooperation/game theory. However, there are still a lot of open problems about cognitive radio from perspective of information theory. In this talk, we will give an overview of the challenges faced by information theory research of cognitive radio, and discuss some potential research topics for future work.

In a dynamic spectrum access system, secondary users try to select their different sensing and transmission parameters to achieve a balance between two conficting goals. The first is to make their activity transmarent to the primary users, while the second goal is maximizing their own throughput. Due to the inevitable occurance of spectrum sensing errors, collisions between primary and secondary transmissions will occur and lead to decreased throughput for both primary and secondary users. In this work, we study the effect of spectrum sensing erros on the system's performance from a stable throughput point of view, and we propose a novel spectrum access strategy that is aware of the spectrum sensing errors and that aims at maximizing the stability region for both primary and secondary users. The design of the access stratgey is formulated as an optimization problem, and different approximations are proposed to simplify the solution of this problem are developed. Our results show that the exact and approximate solutions are very close to each other, and that the proposed strategy offers a significant incrase in the throughput of both primary and secondary users.

Radiotherapy is a common form of tumor treatment in which a patient is subjected to localized radiation from a particle beam aimed directly at a cancerous tumor. To avoid unnecessary damage to healthy tissue, care must be taken to immobilize the tumor during treatment. For tumors of the lung, this is not easily possible due to tumor motion resulting from breathing. In order to mitigate this effect, a robotic couch with feedback control has been proposed to compensate for a patient's breathing signal. Past work on this project is described and future work is outlined.

How to efficiently and fairly allocate data rate among different users is a key problem in the field of multiuser multimedia communication. However, most of the existing optimization-based methods, such as minimizing the weighted sum of the distortions or maximizing the weighted sum of the PSNRs, have their weights heuristically determined. Moreover, those approaches mainly focus on the efficiency issue while ignoring the more important fairness issue. In this paper, we address this problem by proposing a game-theoretic framework, in which the utility/payoff function of each user/player is jointly determined by the characteristics of the transmitted video sequence and the allocated bit-rate. We show that with the proportional fairness criterion, the game has a unique Nash equilibrium, according to which the controller can efficiently and fairly allocate the available network bandwidth to the users. We also show that the traditional optimization-based approach is a special case of the game-theoretic framework with ill-defined utility function. Finally, we show several experimental results on real video data to demonstrate the efficiency and effectiveness of the proposed method.

Cooperative spectrum sensing has been shown to be able to greatly improve the sensing performance in cognitive radio networks. However, all secondary users cooperating in sensing at every time slot may not be optimal, or even difficult if the cognitive users belong to different service providers, where they tend to contribute less in sensing in order to increase their own throughput. In this paper, we propose an evolutionary game framework to study the time evolution of cooperation of the selfish users in spectrum sensing. We derive the behavior dynamics and the evolutionarily stable strategy (ESS) of the secondary users by using replicator dynamics. We then prove that the dynamics converge to the ESS, which renders the possibility of a decentralized implementation of the proposed sensing game. According to the dynamics, we further develop a distributed learning algorithm so that the secondary users approach the ESS only with their own payoff observation. We finally study the possible attacks on the spectrum sensing game and analyze their damages. Simulation results show that the average throughput achieved in the cooperative sensing game is higher than that when the secondary users sense the primary user individually without cooperation. The proposed game is demonstrated to converge to the ESS, and achieve a better system performance than the scheme having all user always contribute to sensing.

The task of separating music into its constituent sources has been a central focus of music information retrieval for many years. Aside from the aesthetic reasons for separating music (e.g., remixing audio), source separation simplifies many other problem domains in music information retrieval such as transcription, audio fingerprinting, cover song retrieval, rhythm representation, and more. Unlike blind source separation in general signal scenarios, musical settings impose further constraints which render these generic solutions obsolete. In this talk, we introduce the use of clustering in the harmonic feature vector domain by using pitch labels as priors. This approach increases the coherency within each separated source over other approaches which do not perform clustering in this domain.

Dynamic spectrum access (DSA), enabled by cognitive radio technologies, has become a promising approach to improve efficiency in spectrum utilization, and the spectrum auction is one important DSA approach, in which secondary users lease some unused bands from primary users. In this paper, we propose a novel multi-winner spectrum auction game to achieve optimal spectrum allocation and high seller's revenue. As secondary users may be selfish in nature and tend to be dishonest in pursuit of higher profits, we develop effective mechanisms to suppress their dishonest/collusive behaviors when secondary users distort their valuations about spectrum resources and interference relationships. Moreover, in order to make the proposed game scalable when the size of problem grows, the semi-definite programming (SDP) relaxation is applied to reduce the complexity significantly. Finally, simulation results are presented to evaluate the proposed auction mechanisms, and demonstrate the complexity reduction as well.

In this talk, a new communication paradigm, namely "Wireless Network Cocast (WNC)", is proposed. WNC utilizes cooperative communication and linear network coding to achieve desired diversity order with low transmission delay and low cost. In particular, for a network of N nodes, a diversity order N is achieved with only 2N time slots, a significant improvement in comparison with a conventional cooperative communication scheme, namely maximal cooperation (MAX), which requires NxN time slots for diversity order of N. Talk starts with defining the problem with direct transmission (DTX). Then current solutions using relay tower and cooperative communication are presented and their shortages are discussed. The discussion provides the motivation for the new approach WNC. The transmission structure of WNC with linear network coding is then presented, the performance is analyzed, and simulation reveals its advantageous performance. A number of WNC applications are also presented. In particular, location-aware WNC and WNC with relay tower will be discussed. At the end, the talk is concluded by providing the advantages of WNC.

Digital fingerprinting is an emerging technology that offers proactive post-delivery protection of multimedia. Multiuser collusion attack is a powerful attack against digital fingerprinting, where a group of attackers collectively mount attacks to attenuate the identifying marks. When the collusion-resistant forensic code is applied onto multimedia content, the colluders usually perform post-processing on the colluded multimedia content before redistribution. The post-processing incurs error in the detected bits of the forensic code and posts a new challenge to the forensic code design. We designed the anti-collusion and post-processing resistant binary forensic by concatenating orthogonal codes with low correlation Reed-Solomon code. The simulation results shows that our forensic code design can achieve perfect detection when the number of colluders is less than 5 and up to 45% of the forensic code is changed for a five-minute video clip.

Traditional wireless communication techniques cannot handle severe multipath and scattering as they cannot know precisely the channel impulse response. In this talk, we present a new technique - RF time-reversal architecture (RF-TRA), in which the RX sends an impulse into the system and hence the TX obtains perfect channel impulse response, provided the channel is reciprocal. Based on the channel response, the TX sends a reconstructed signal which automatically focuses power back to the RX. The implementation of RF-TRA system relies on high speed sampling ADCs/DACs and high speed signal processing on FPGA. We also show that it is possible to build up a preliminary demo at a lower data throughput using the Universal Software Radio Peripheral (USRP) board and GNU Radio.

Digital images, as well as digital image editing software, have become pervasive in today’s society. As a result, it has become necessary to develop a family of tests to determine if a digital image has been manipulated, or if it exists in an unaltered state. One forensically important image alteration is the insertion of additive noise into an image. While this operation itself may not alter the perceptual content of an image, it can be used to effectively mask traces of other tampering operations. In this talk we present a blind method to detect the insertion of additive noise into a digital image. This method operates by determining the presence and strength of statistical artifacts which arise in an image due to the insertion of additive noise. Simulation results for the proposed detection scheme indicate that a probability of detection in excess of 95% can be achieved for a probability of false alarm below 3%.

Vehicular Networks are an emerging type of networks in which vehicles and roadside units are the communicating nodes; providing each other with information, such as safety warnings and traffic information. As a cooperative approach, vehicular communication systems can be more effective in avoiding accidents and traffic congestions than if each vehicle tries to solve these problems individually. In this talk, we will give a general overview of vehicular networks and there applications, the enabling technologies and will identify some interesting research issues for future work.

In this talk, we investigate impact of jamming attacks on cognitive radio networks, a very important yet rarely discussed problem. We assume a secondary network coordinated by a secondary base station is attacked by an energy-limited jamming attacker. The M/G/1 queue with vacation model is employed to provide quantitative analysis on damages in terms of average waiting time and blocking probability. When the traditional collaborative sensing scheme is used, malicious attackers can easily capture the slot pattern by monitoring the spectrum. Then, they can launch efficient attacks by jamming the sensing phase only. In order to make the cognitive radio networks more robust to malicious attacks, we propose a frequency-hopping collaborative sensing scheme to alleviate the damages caused by energy-limited attackers.

In this talk, we investigate the relationship between risk and distortion for the linear video collusion attack with Gaussian fingerprint. By modelling the residue, i.e. the different between temporal adjacent frames, as a Gaussian distribution, we express the risk and distortion as functions of the temporal filter coefficients. By adjusting the coefficients, we are able to find the minimal distortion under a pre-defined risk constraint. We show that, given a fixed false alarm probability \alpha, when the risk is not larger than \alpha, the globally optimal coefficient can be found by solving a convex optimization problem using numerical method, e.g. interior points method. When the risk is larger than \alpha, the problem of finding the globally optimal coefficient is not convex (with a convex objective function but concave-convex constraints). However, the locally optimal coefficient can be found by the constrained concave-convex procedure (CCCP). Using the optimal coefficient (either globally or locally), an implicit risk-distortion model can be obtained. Furthermore, we derive an explicit risk-distortion mode by assuming the variance of the residue (a quadratic form of the coefficients) is around a constant, e.g. \beta. We also discuss the optimal detection and attack with side information. Finally, we conduct several experiments to verify the proposed risk-distortion model using real video data.

Cooperative spectrum sensing has been shown to greatly improve the sensing performance in cognitive radio networks. However, if the cognitive users belong to different service providers, they tend to contribute less in sensing in order to achieve a higher throughput. In this paper, we propose an evolutionary game framework to study the interactions between selfish users in cooperative sensing. We derive the behavior dynamics and the stationary strategy of the secondary users, and further propose a distributed learning algorithm that helps the secondary users approach the Nash equilibrium with only local payoff observation. Simulation results show that the average throughput achieved in the cooperative sensing game with more than two secondary users is higher than that when the secondary users sense the primary user individually without cooperation.

With the explosion of digital music distribution and sharing over the past decade, the growth of huge musical databases have created a need for fast and accurate information retrieval and classification of music. However, due to a lack of consensus among music listeners over the definition of various genres, automatic classification remains a difficult task. Today, we will discuss methods used for classification of musical genres and artists using supervised methods along with the correspondence between feature extraction and musical properties such as timbre, rhythm, and harmony. The results of our feature extraction will be shown in conjunction with supervised classification methods such as support vector machines, linear discriminant analysis, and K-nearest neighbor search.

A detection problem in sensor networks is considered where sensor nodes are modeled on two concentric circles and receive partial information about their environment. The nodes transmit their observations over a noisy channel to the fusion center for the purpose of detection. In this work, we study the system performance as a function of sensor density which allows us to explore the natural tradeoff between the total number of sensor nodes and the quality of information. In dense sensor networks with spatially correlated sensors, it is likely that sensors within a close vicinity of each other would observe highly correlated data. While conditional independence is a convenient and widely used assumption, it is likely to fail in such a dense network. So, instead of competing for resources and causing network congestion, highly correlated sensors should cooperate and share the use of transmission channels for optimal data gathering. Our analysis is evaluated in terms of the probability of detection error for different simple scenarios in order to characterize the effect of inter-sensor separation into the selection of sensors/relays for cooperation.

The development of powerful image editing software such as Adobe Photoshop has made it possible to construct inauthentic images that are visually realistic. In response, a need has arisen for the development of techniques which can identify tampering in digital images. Digital watermarking technologies are often ill suited to address this problem because they require insertion of the watermark before tampering has occurred. Other existing tamper identification techniques require either knowledge of the device used to generate the image, or a large training dataset of images from the same source. In this presentation, we propose a new method which detects image forgeries using no a priori knowledge of the image or digital capture device. This method operates by detecting statistical artifacts left behind by nonlinear pixel mappings involved in creating the digital forgery. A full description of the detection algorithm, as well as simulation results are presented in this talk.

In order to fully utilize spectrum, auction-based dynamic spectrum allocation has become a promising approach which allows unlicensed wireless users to lease unused bands from spectrum license holders. Because spectrum resources are reusable by users far apart, in some scenarios, spectrum is more efficiently utilized by awarding one band to multiple secondary users simultaneously, which distinguishes it from traditional auctions where only one user can be the winner. However, the multi-winner auction is a new concept posing new challenges in the traditional auction mechanisms, because such mechanisms may yield low revenue and are not robust to some newly-emerging collusion. Therefore, in this paper, we propose an efficient mechanism for the multi-winner spectrum auction with collusion-resistant pricing strategies, in which the optimal spectrum allocation can be solved by binary linear programming and the pricing is formulated as a convex optimization problem. Furthermore, a greedy algorithm is proposed to reduce complexity for multi-band auctions. Simulation results are presented to evaluate our proposed auction mechanisms.

The basic idea behind oppotunistic spectrum access is to allow secondary users to search and exploit instanteneous spectrum opportunities while limiting the level of iinterference perceived by primary users. Due to noise and fading, spectrum sensing errors are inevitable. These errors results in increased interference to primary users and decreased throughput for secondary users. Therefore, interaction between physical layer sensing and MAC layer access starategies always exist. In this work, we study this interaction and propose a joint design of spectrum sensing and channel access protocols. Our design is analyzed from a queuing theory point of view, and numerical results are used to demonstrate significant throughput improvements using our joint design method.

In wireless sensor networks, reducing total transmit power, required by all sensors to send their information to the sink, is one of the key design issues. In addition, having an even distribution of transmit power among sensors increases network lifetime. Typically, the information gathered from different sensors is spatially correlated to each other. Conventional information aggregation schemes, making use of this information correlation, require high total transmit power and achieve unfair power distribution. In this paper, we propose cooperation-based information aggregation schemes that utilize cooperative communication to reduce the transmit power and achieve even power distribution. We show that by utilizing cooperative communication among sensors, our proposed schemes yield more than 67% in power reduction for any network sizes. For network sizes greater than 5 sensors, the power reduction is more than 90%. In addition, the transmit power is more uniformly distributed in our proposed schemes.

Cooperative communication can be used to reduce the transmit power of distant mobile units, compared to conventional direct transmission, given the same quality-of-service. However, imposing the constraint of having orthogonal transmission for the source and relays leads to large delay in TDMA systems. For a network of $N$ mobile units, the transmission delay would be N(N+1)/2. In this work, we propose a location-aware cooperation-based scheme that aims to reduce transmit power of distant mobile units while maintaining a low transmission delay. The scheme utilizes a linear network coding protocol, where each mobile unit applies linear network coding to a set of transmit symbols that it has received previously. At the base station, multiuser detection is used to decouple the transmit symbols. Both decode-and-forward and amplify-and-forward cooperative protocols are considered. We show that our proposed scheme achieves a comparable bit-error-rate performance with the conventional cooperation-based TDMA scheme while requiring a delay of (2N-1) time slots, a substantial reduction in the transmission delay.

The prevalence of digital audio editors in today's society allow us to conveniently and efficiently record and edit music. Unfortunately, these editors also enable malicious users to create digital audio forgeries more easily than ever before. In recent cases of audio forgery, attackers use an existing audio file, perform little or no modification upon the file, and then call the file as their own. In this talk, we propose a novel and effective detection strategy which allows us to accurately match forged audio signals to their original sources. Aside from forgery detection strategies, our contributions include the examination of attacks at the signal level, use of attack-invariant feature extraction, performance improvements via pattern classification methods, and comparison against existing audio fingerprinting systems.

In this work, we investigate the impact of the cooperative communications on the self-noise problem in cellular networks. The self-noise phenomena expresses the portion of the transmission power that contributes to the noise due to channel estimation errors. First, we derive the outage probability for the direct and cooperative transmission scenarios taking into consideration the self-noise problem. We show that the outage probability reduces by utilizing cooperative communication protocols. Second, we derive the signal-to-noise ratio (SNR) gap ratio, which measures the relative SNR gap due to the self-noise problem. We show that the decode-and-forward cooperative scheme is less susceptible to the channel estimation errors compared to the direct transmission one. Finally, we investigate the effect of the self-noise problem on relay-selection cooperative and multi-path direct transmission schemes.

In this paper, a spectrum sharing scheme that will coordinate among different co-existing cellular operators competing for the same spectrum band is proposed. Based on this scheme, the cell of an operator can be divided into several sub-regions, and mobile stations (MSs) inside each sub-region form one subset. The whole frequency band assigned to a cell is partitioned into slots dedicated to the subsets based on the Quality of Service (QoS) demand. When interference from other operators is detected, the victim operator can switch the frequency of the interfered MSs with the MSs in the safe region, and/or switch to the reserved band. In this way, the inter-operator interference (IOI) can be reduced. From the simulation results, it is shown that with the proposed protocol, the total power consumption of both operators can be reduced significantly. Furthermore, it has been demonstrated that in order to reduce the IOI in a high-density area, the operator should reserve more bandwidth for potential frequency-switching.

Multimedia social network analysis is a research area with rising importance, which analyzes the behavior of users who share multimedia content and investigates the impact of human dynamics on multimedia systems. Members in peer-topeer live-streaming social networks cooperate with each other to provide a distributed, highly scalable and robust platform for live streaming applications. Since every member has different upload/download bandwidth, to accommodate better service, scalable video coding should be used, which challenges best chunk-request strategy. We propose a cheat-proof optimal strategy for 2 user case and extend it to multiple user scenario.

Cooperative communications and spectrum sharing, originally considered as separate problems, are in fact dual problems in the sense that he available unused or under-used channel resources can be utilized to enhance the primary system performance via cooperation, or it can e shared by a secondary system to transmit new information. In this work, we propose a multiple access protocol that enables both relays helping primary users, and secondary to coexeist and share the free available resources in the network. We provide analytical and simulations results for the throughput and delay performance of the proposed protocol.

Cognitive radio is a candidate technology for more efficient spectrum utilization systems based on opportunistic spectrum sharing. Because this technology does not rely on traditional license-based spectrum allocation policies, it could disrupt existing systems if the spectrum utilization decision is based on unreliable spectral estimation. Today, we are going to investigate the concept of cooperative spectrum sensing in fading channel based on distributed spectrum sensing. We also considered the security problem in cooperative spectrum sensing. We proposed a new algorithm to identify the presence of attackers and eliminate their effect on the system.

Due to the prevalence of digital cameras and photo editing software, it has become increasingly difficult to determine if a digital image has been altered. Often, alterations to a digital image will leave behind statistical artifacts which can be detected by a third party. In this talk I will propose a blind detection scheme to determine if a global contrast enhancement operation has been used to alter a digital image. In addition a separate blind detection will be proposed for a specific enhancement operation known as histogram equalization. The design procedure and performance of both detection schemes will be discussed.

Recent cases of audio forgery have been uncovered within the past year, taking the audio community by surprise. In these types of cases, the attacker uses an existing audio file, performs little to no modification upon the file, and then calls the file as his or her own. In this talk, we describe more sophisticated attacks on digital audio at the signal level that result in a large distance between the original and attacked audio, thus avoiding basic quantitative matching methods. Canonical parameterization of sinusoids -- phase, frequency, and amplitude -- are investigated, along with other attacks. Then we offer detection strategies based on audio registration which can perform where quantitative matching or audio fingerprinting/hashing fails.

In this paper, we address the network maintenance problem where we aim to maximize the lifetime of a sensor network by adding a set of relays to it. The network lifetime is defined as the time until the network becomes disconnected. The Fiedler value, which is the algebraic connectivity of a graph, is used as an indicator of the network health. First, we present a network maintenance algorithm that obtains the best locations for a given set of relays. This algorithm depends on formulating the search problem as a standard semi-definite programming (SDP) that can be solved efficiently. Second we propose a routing algorithm, namely, Weighted Minimum Power Routing (WMPR) algorithm, that significantly increases the network lifetime due to the efficient utilization of the deployed relays. Third, we propose an adaptive network maintenance algorithm that relocates the deployed relays based on the network health indicator. We show that the proposed algorithms achieve network lifetime gain of 449.5% by adding 4 relays to a sensor network of 20 nodes. Finally, we consider the network repair problem, in which we find the minimum number of relays along with their best locations to reconnect a disconnected network. We propose an iterative network repair algorithm that utilizes the network maintenance algorithm.

In this talk, the problem of distributed detection in wireless sensor networks is considered. A system consisting of a set of sensor nodes communicating to a fusion center, where decisions are made, is considered. We consider the problem of employing relay nodes in the sensor networks by assigning some of the system resources for relaying the information from some of the sensor nodes. As some sensor nodes provide ``less-informative" measurements to the fusion center, we consider reassigning the system resources allocated for these sensors to relay nodes to forward the measurements of the ``more-informative" sensor nodes. There will be a trade-off between the number of measurements sent to the fusion center and the reliability of the more-informative measurements. We will analyze the performance of two protocols, namely, Protocol I and Protocol II. In Protocol I, each sensor node directly transmits its measurement to the fusion center. In Protocol II, some of the sensor nodes relay the measurements of other more-informative sensor nodes. Hence, in Protocol II, the reliability of the more-informative measurements is enhanced at the expense of having less measurements sent to the fusion center and this creates the trade-off between the number of measurements and the reliability of the measurements. We analyze the performance of the two protocols over additive white Gaussian noise (AWGN) and Rayleigh fading channels. Based on the analysis, we characterize the regions where the performance of one protocol is superior the other. The results show that in some cases it is better to allocate some of the system resources to relay nodes, not to sensor nodes, to increase the reliability of the more-informative measurements and this leads to a better overall detection performance at the fusion center.

Game theoretical approaches have been shown powerful to achieve distributed resource allocation in wireless networks. However, most of them are based on the concept of Nash Equilibrium (NE), which is generally not system efficiency. Therefore, in this paper we develop a correlated equilibrium (CE) framework for distributed resource allocation in a variety of wireless networking scenarios, such as multiple access control, sensor/ad hoc networks, and dynamic spectrum access networks. Using the CE strategy, wireless users can cooperate on the joint distribution of the actions so as to achieve mutual benefits, which is much better than that of NE strategies. We target to answer two questions: how to utilize the CE concept to model the resource allocation problems, and how to achieve the optimal CE. We first investigate and analyze the properties of the CE convex hull. Then, no-regret learning algorithm is shown, and we further propose a heuristic algorithm allowing limited information exchange among wireless mobile users. From the simulation results, we show that compared with the no-regret learning algorithm, the proposed heuristic learning algorithm not only can achieve better aggregated expected utility, but also converge with a higher speed with small extra signaling overhead.

The unlicensed spectrum sharing problem is modeled into game theoretic framework. By using the punishment based repeated game, wireless users can automatically maintain some kinds of cooperations, resulting in an more efficient usage of the spectrum. Several cooperation rules are proposed. Furthermore, we propose a mechanism design method to give the users the incentive to reveal their private information truthfully all the time.

Modulation forensics is to detect the modulation type in wireless communications without any prior information. It finds both military and civilian applications such as surveillance and cognitive radio. It is a challenging task, especially in a non-cooperative environment, as no prior information on the incoming signal is available at the receiver. In this paper, we investigate the modulation forensics of linear digital modulations and space-time orthogonal code in slowly varying frequency-selective fading channels. With unknown channel vector, and phase distortion at the receive-side, we derive a composite test consisting second-moment nonlinearity and maximum likelihood test, and discuss the performance and forensic system confidence measure. It is shown that the proposed algorithm achieves almost perfect identification of the space-time coding, and high accuracy rate of modulation type detection.

This tutorial will address Multiple Input Multiple Output (MIMO) and related emerging Cooperative Communications technologies and their potential military applications. Both MIMO and Cooperative Communications have the potential to provide enhanced performance capabilities in challenging RF environments such as urban, subterranean and any environment where multi path is a factor. This tutorial will provide an overview of these technologies and address the challenges of incorporating them in a military environment to include mobility issues, size, weight and power, and other factors unique to the military environment. The tutorial will address areas that US Army CERDEC has an interest in pursuing further research and transition of the technology to future communications platforms.

In this work, we revisit the forensic problem of source coder identification for digital images. We extend our earlier work which offered analysis and detection of intrinsic fingerprints generated by lossy image source coders. The new aspect to consider is the presence of multiple instances of compression in a digital images. Such a scenario is common in many typical image processing datapaths. By analyzing quantizers of various complexity applied to various signals, we offer conditions where multiple compression becomes detectable, as well as additional measures one can perform to improve the identifiability of multiple compression.

Cognitive radio is a candidate technology for more efficient spectrum utilization systems based on opportunistic spectrum sharing. In a dynamically changing spectrum environment, it is very important to consider the statistics of different users' spectrum access so as to achieve more efficient spectrum allocation.

In this work, we propose a modification for the primary-prioritized Markov approach for dynamic spectrum access which is based on modeling the interactions between the primary and the secondary users as continuous-time Markov chains (CTMC). By optimizing the access probabilities for each secondary user, we can improve the performance more than the original proposed algorithm.

In the second talk, we are going to introduce our testbed used for cognitive radio algorithms implementation. This testbed consists of 2 Universal Software Radio Peripheral (USRP) boards and a PC running GNURadio on Ubuntu Linux. We will demonstrate two experiments we have recently done.

In a network, most of the sources are bursty in nature, which leads to periods of silence in which users may have no data to transmit. These periods of silence result in under-utilization of the channel resources. Cooperative communications and spectrum sharing, originally considered as separate problems, are in fact dual problems in the sense that the available unused or under-used channel resources can be utilized to enhance the primary system performance via cooperation, or it can be shared by a secondary system to transmit new information. In this work, we try to investigate the possibility of dividing network free resources between secondary users to transmit their own information and relays to help both primary and secondary users.

We consider the trans-modulation design for the decode-and-forward relay networks. We propose to reassign the constellation points at the relay nodes in such a way that the symbol error rate (SER) at the destination node is minimized. The proposed trans-modulation scheme can significantly improve the system SER performance without increasing the complexity of the system, especially when the relays are close to the source. For this case, improvements of about 2 dB for 16-QAM constellation and about 3 dB for 64-QAM constellation are achieved for the single relay case.

Several works have considered the design of distributed detection schemes in sensor networks. Most of these works have focused on having a network power or rate constraint. Most of them have focused on characterizing the performance in terms of "error exponent" (which is the rate of decay of some probability of error as the number of sensors or observations tends to infinity). In this talk, I will present some preliminary results on a different issue, whether it is better to use the sensor to sense or as a relay at a certain location in the network. The idea is that sensors that sense "less informative" data can better work as relays. In this talk, I will present the case of Gaussian observations over AWGN channels.

EKG stands for electrocardiogram. It is the signal of electrical voltage in the heart. One important piece of information we can get from the EKG signal is the Heart Rate Variability (HRV). HRV describes how the heart rate changes along time, or how the time interval between consecutive heart beats changes along time. Heart rate is controlled by the human automatic nervous system, which responds to stress, pain, and various other physical conditions. The ultimate goal of this study is to find correlation between a patient’s HRV and how much pain the patient is suffering, and to apply this correlation to assist diagnosis of children with asthma. As a first step toward our goal, we develop a method to detect heart beats from EKG signals, which is also referred as QRS detection in the literature. This is an old problem. In this talk, I’ll present a new solution based on p-spectrum. The results show that the proposed method yields excellent detection performance (99%). Although the performance is comparable with that of existing methods, the proposed method has its advantages, such as do not require predetermined parameters, do not make assumptions on shape of the EKG signal, do not require any training, and can operate in real-time.

Cooperative communications and cognitive spectrum sharing are new techniques that emerged recently with the aim of efficient utilization of network resources. Cooperative communications allow different users to share their resources for distributed transmission of informations. On the other hand, cognitive spectrum sharing techniques allow a secondary system to opportunistically share the spectrum of the primary licensed users when it is idle. So far, these two pradigms have been studied independently. In this work, we try to investigate the possibility of dividing network free resources between relays for cooperative transmission and secondary users to transmit their own information. We characterize the stable throughput region of the new system and study the tradeoff between allocating resources for cooperation and spectrum sharing.

This afternoon, we will give our practice talks in preparation for ICASSP 2007.

Cooperative communications is a new communication paradigm in which different terminals in the wireless network share their antennas and resources for distributed transmission and processing. Recent studies have shown that cooperative communications can yield significant performance improvement due to spatial diversity gains. The theory of cooperative communications is however still immature to fully understand its broader impacts on the design of future wireless networks. This thesis contributes to the advancement of cooperative communications by developing and analyzing cooperation protocols at different network levels, with the goal to provide significant improvements in signal reliability, coverage area, network throughput, and energy efficiency with respect to other existing alternatives.

Network connectivity is necessary for successful communication among the network's nodes. In this paper, we address the problem of network maintenance in wireless sensor networks, i.e., improving the network connectivity by adding an arbitrary set of relay nodes to it. In particular, we try to find the optimum locations for these relays in order to maximize the network connectivity. We characterize the network connectivity by the Fiedler value, which is the second smallest eigenvalue of the Laplacian matrix representing the network graph. We formulate a relaxed version of of this problem as a semi-definite programming problem (SDP) and find a near-optimum solution to it. We show that the proposed algorithm enhances the Fiedler value by 60% due to adding one relay only. Finally, we show that our proposed algorithm can also be used in some cases to find the optimum location for a single relay in order to reconnect a disconnect network.

Image segmentation is an area of research that has existed for a few decades now, with applications covering many aspects of computer vision and pattern recognition. Today, we discuss another problem which is intimately related to image segmentation, namely, detection of cut-and-paste forgeries in digital images. Recent work in the computer vision field has resulted in new optimization-based approaches for achieving image segmentation which depart from traditional approaches. Drawing from this body of work along with our own recent work in source coding forensics, we offer an optimization-based method for detecting cut-and-paste forgeries based upon compression-related feature selection. We will present a thorough discussion of the problem formulation along with results.

Designing diversity achieving schemes over the wireless multi-path fading relay channels is crucial to achieve high performance gains. These gains are achieved by exploiting the multi-path (frequency) and cooperative diversities to combat the fading nature of wireless channels. In this talk, the design of distributed space-frequency codes (DSFCs) for wireless relay networks is considered. The term distributed comes from the fact that the space-frequency code is distributed among randomly located relay nodes. The proposed DSFCs are designed to achieve maximum diversity over the wireless relay channels. A two-hop system model, where there is no direct link from the source node to the destination node, is considered. We consider the use of DSFCs with the decode-and-forward (DAF) and amplify-and-forward (AAF) protocols. The code design criteria to achieve full diversity and maximum coding gain based on minimizing the pairwise error probability (PEP) are derived. For DSFC with the DAF protocol, the proposed DSFCs are proved to achieve full diversity of order LN where N is the number of relay nodes and L is the number of paths per channel. For DSFC with the AAF protocol, the proposed DSFCs are proved to achieve full diversity of order LN for any number of relays, N, for the special cases of L=1 (flat fading) and L=2 (two-rays channel model).

Dynamic spectrum access has become a promising approach to fully utilize the scarce spectrum resources. In a dynamically changing spectrum environment, it is very important to consider the statistics of different users' spectrum access so as to achieve more efficient spectrum allocation. In this paper, we propose a primary-prioritized Markov approach for dynamic spectrum access through modeling the interactions between the primary and the secondary users as continuous-time Markov chains (CTMC). Based on the CTMC models, to compensate the throughput degradation due to the interference among unlicensed users, we derive the optimal access probabilities for the unlicensed users, by which the spectrum access of the unlicensed users is optimally coordinated, and the spectrum dynamics are clearly captured. Therefore, a good tradeoff can be achieved between the spectrum efficiency and fairness. The simulation results show that the proposed primary-prioritized dynamic spectrum access approach under proportional fairness criterion achieves much higher throughput than the CSMA-based random access approaches and the approach achieving max-min fairness. Moreover, it provides fair spectrum sharing among unlicensed users with only small performance degradation compared to the approach maximizing the overall average throughput.

In recent years, high throughput measuring techniques (gene microarrays, protein mass spectrum) have made it possible to simultaneously monitor the expression of thousands of genes or proteins. A topic of great interest is to study the difference of gene/protein expressions between normal and cancer subjects. In literature, various clustering methods have been proposed to analyze gene/protein data, and they are dominantly data-driven. In our work, we proposed an alternative model-driven approach. Our aim is to develop statistical models to systematically interpret the high throughput experiment data and reveal biology insights. We propose a dependence model which can be used to examine the interactions among genes/proteins: we can zoom out to study the big picture, the ensemble dependence relationships among groups of genes/proteins; we can also zoom in to examine the details, the relationship among individual genes/proteins. We have shown that the dependence model is highly effective in the classification of data from normal and cancer subjects. We discovered that the eigenvalue of the dependence model exhibits different patterns for normal and subjects at different stages of cancer development. This indicates the dependence model has the potential to predict cancer development. The concept of dependence network is proposed based on the dependence model. The interaction relationships among genes/proteins are modeled by the dependence network, from which we are able to reliably identify biomarkers, important genes/proteins for the early prediction and effective treatment of cancer.

Dynamic spectrum allocation becomes a promising approach to increase the spectrum efficiency for wireless networks. However, the collusion among selfish network users may seriously deteriorate the efficiency of dynamic spectrum sharing. In this paper, we model the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. In order to combat user collusion, we propose a pricing-based collusion-resistant dynamic spectrum allocation approach to optimize overall spectrum efficiency while not only keeping the participating incentives of the selfish users but also combating possible user collusion. The simulation results show that our proposed scheme achieves high efficiency of spectrum usage even with the presence of severe user collusion.

Our purpose is to develop a statistical modeling approach for cancer biomarker discovery and provide new insights into early cancer detection. We propose the concept of dependence network, apply it for identifying cancer biomarkers, and study the difference between the protein or gene samples from cancer and non-cancer subjects based on mass-spectrometry (MS) and microarray data. Three MS and two gene microarray datasets are studied. Clear differences are observed in the dependence networks for cancer and non-cancer samples. Protein/gene features are examined three at one time through an exhaustive search. Dependence networks are constructed by binding triples identified by the eigenvalue pattern of the dependence model, and are further compared to identify cancer biomarkers. Such dependence-network-based biomarkers show much greater consistency under 10-fold cross-validation than the classification-performance-based biomarkers. Furthermore, the biological relevance of the dependence-network-based biomarkers using microarray data is discussed. The proposed scheme is shown promising for cancer diagnosis and prediction.

Traditional approaches to multimedia security (e.g. watermarking, cryptography) protect content using additive operations. With these methods, we require access to the original host signal. However, in many scenarios, we may not even have access to the host signal, and therefore we cannot enforce protection through any extrinsic means. With non-intrusive forensic analysis, the forensic analyst only has access to an output signal in a raw format, without any header information or metadata.

In this talk, we propose a method to identify the presence of source coding performed upon a digital image. By analyzing the artifacts left behind, we can identify the history of operations, including pre-processing, transformation, and quantization. We employ a probability-based distance measure to classify the method of transform coding previously performed upon the image, and we show results across a variety of transform methods, quality factors, and additive noise.

Speech communication is characterized by periods of silence in between talk spurts that account for roughly 60 % of the conversation time. This is a key property that, when exploited, could significantly improve the utilization of channel resources but at the cost of requiring a more sophisticated multiple access protocol. For wireless channels, these issues are addressed in the Packet Reservation Multiple Access (PRMA) protocol. Unfortunately, transmission errors inherent to wireless communications significantly impact the performance of PRMA. To mitigate the negative channel effects on the protocol, we propose the deployment of a relay terminal in the PRMA network. The relay will utilize a fraction of the free resources available in the network (due to silence periods) to introduce spatial diversity without sacrificing the bandwidth efficiency of the system. Analytical and numerical results reveal a significant improvement in the network throughput and the perceived speech quailty over the non-cooperative protocol.

Multi-user collusion is a cost-effective attack against digital fingerprinting, in which a group of attackers collectively undermine the traitor tracing capability of digital fingerprints. However, during multi-user collusion, each colluder wishes to minimize his/her own risk and maximize his/her own profit, and different colluders have different objectives. Thus, an important issue during collusion is to agree on how to distribute the risk/profit among colluders and ensure fairness of the attack. To have a better understanding of the attackers' behavior during collusion to achieve fairness, we model the dynamics among colluders as a non-cooperative game. We then study the Pareto-Optimal set, where no colluder can further increase his/her own payoff without decreasing others', and analyze the Nash Bargaining solution, and also other solutions of this game.

Today's wireless networks are regulated by a fixed spectrum assignment policy, which doesn't efficiently utilize the limited available spectrum resources. Dynamic spectrum access is proposed to solve these current spectrum inefficiency problems. Among branches of the dynamic spectrum access, secondary usage of the licensed spectrum is a viable solution to more efficient utilization of the frequency spectrum. This means, when certain spectrum is not currently used by any primary user, unlicensed users share this spectrum opportunistically. However, when primary users re-appear, the unlicensed users on the same spectrum should vacate. How to combine the primary user activity for opportunistic spectrum allocation is still an open issue. In this work, a continuous time Markov chain (CTMC) is presented to model the dynamics of the system's evolvements. The limiting behaviors of the primary user and unlicensed users are characterized. A proportional fair (PF) opportunistic spectrum access scheme is proposed to efficiently and fairly assign the spectrum access to the unlicensed users. Finally, simulation studies are provided to justify the proposed scheme.

Recently, the merits of the cooperative communications in the physical layer have been explored. However, the impact of the cooperative communications on the design of the higher layers is not well-understood yet. In this paper, we consider the power-efficient cooperative routing problem in wireless ad hoc networks, which exploits the features of the wireless medium. We propose the Minimum Power Cooperative Routing (MPCR) algorithm, which requires polynomial complexity. The MPCR algorithm constructs the minimum-power route as a cascade of the minimum-power single-relay building blocks from the source to the destination. Thus, any distributed routing algorithm can be utilized to find the optimal route with minimum end-to-end transmitted power, while guaranteeing certain throughput. The simulations show that the MPCR algorithm can achieve power saving of 9.3% compared to the existing cooperative routing algorithm, where the selected routes are constructed based on the noncooperative routes.

A key challenge in the design of real-time wireless multimedia systems is the presence of fading coupled with strict delay constraints. A very effective answer to this problem is the use of diversity achieving techniques. This talk focuses on studying systems that exhibit diversity of three forms: source coding diversity, channel coding diversity and user-cooperation diversity (implemented through either relay channels or multi-hop channels, each with amplify-and-forward or decode-and-forward user cooperation). Consistent with the focus on real-time multimedia communications, performance is measured through the distortion exponent, which measures the rate of decay of the end-to-end distortion at high SNRs. The results show that for both relay and multi-hop channels, optimum channel coding diversity provides the best performance, followed by source coding diversity. The results also show a tradeoff between the quality (resolution) of the source encoder and the amount of cooperation, in that, as the bandwidth expansion factor increases (higher bandwidth) user cooperation diversity is the main limiting factor, not the source encoding distortion. Thus, the distortion exponent is improved by increasing the number of relays (increasing the diversity order). At low bandwidth expansion factor the source average end-to-end distortion is limited by the source encoder distortion and, in this case, using higher resolution source encoder will improve the performance (in terms of the distortion exponent) more than increasing the number of relay nodes.

There are many important criteria in designing algorithms in sensor network, namely energy efficiency, energy awareness, topology awareness, and connectivity awareness, etc. Among all those criteria, the network connectivity is a very important one, since most of the sensors in the sensor network are static and they stay in their original position for the entire of their lifetime. Therefore, it is important to design a robust metric that characterizes the network connectivity. In this talk, we will explain how to model the connectivity of the network using the spectral of the graph. We propose link models. We also provide 2 applications, namely routing and network health maintenance. In both applications, we show how the spectral of graph can be used to derive the connectivity-aware solution.

The gains of cooperative communications in wireless networks have been explored recently under the ideal assumption of negligible receiving and processing power. In sensor networks, the power spent for listening and computing can constitute a significant portion of the total consumed power, and such an overhead can reduce the gains promised by cooperation. In this work, cooperation gains are investigated by taking into consideration such overheads in the analytical framework. The performance metric considered is the energy efficiency of the system measured by the total power required to achieve a certain quality of service requirement. The analytical and numerical results reveal very interesting threshold behavior below which direct transmission is more energy efficient, and above which cooperation provides more gains. Such a tradeoff is shown to depend on many parameters such as the relative locations of the source and destination, the values of the receive and processing powers, the application, and many other factors. Moreover, there are experimental results conducted to verify the channel model.

PRMA is an efficient statistical multiplexing scheme which combines random access with time division. It allows a group of spatially dispersed terminals to transmit packetized voice to a common base station over a shared channel. In this scheme, transmission errors have a significant impact on the system capacity and speech quality. In this work, we add user cooperation capability to the PRMA protocol to improve system performance. We exploit the on/off characteristic of speech to allow some of the users to act as relays for other users. In the talk, a detailed Markov analysis of our proposed protocol will be presented, using this analysis we are able to compute system capacity, access delay and packet dropping probability.

Multimedia security, in all its forms, is a broad field devoted to protecting the content of data through such approaches as cryptography, watermarking, fingerprinting, and network security. However, in the absence of such security schemes, there does not exist any artificial signals or operations added to the image to enforce protection. Today, we explore a growing field of multimedia forensics known as non-intrusive forensic analysis, where the forensic analyst only has access to the output data in a raw format, without any header information or metadata. In performing forensic analysis, we can achieve many objectives such as datapath integrity and patent enforcement. We present a non-intrusive forensic methodology related to the identification of source coding for images, including the detection of pre-processing, transform method, and quantization method. This methodology can be applied to a wide variety of images encoded using one of many families of encoders, including transform-based, predictive, vector quantization, and fractal coders.

The performances in cooperative communications depend on careful resource allocation such as relay selection and power control, but traditional centralized resource allocation needs considerable overhead and signaling to exchange the information for channel estimations. In this paper, we propose a distributed buyer/seller game theoretic framework over multiuser cooperative communication networks to stimulate cooperation and improve the system performance. By employing a two-level game to jointly consider the benefits of source nodes as buyers and relay nodes as sellers, the proposed approach not only helps the source smartly find the relays at relatively better locations and buy optimal amount of power from them, but also helps the competing relays maximize their own utilities by asking the reasonable prices. The game is proved to converge to a unique optimal equilibrium. From the simulation results, the relays in good locations can play more important roles in increasing source node's utility, so the source would like to buy more power from these preferred relays. On the other hand, the relays have to set the proper prices to attract the source's buying because of competition from other relays and selections from the source. Moreover, the distributed game theoretic resource allocation can achieve comparable performance compared with the centralized one.

In many signal processing, it's important to determine if the source is the desired one. In this paper, we'll present a method to identify the source coding scheme given a distorted picture. Our system can achieve identification rate over 95% for a PSNR between 20 dB and 35 dB, and identification rate over 80% for a PSNR between 35dB and 40dB. Also our system gives a confidence measure of our result.

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. By studying the selfish users' collusive cheating behaviors, a robust and efficient dynamic pricing approach is proposed to optimize overall spectrum efficiency while not only keeping the participating incentives of the selfish users but also combating possible user collusion. The simulation results show that our proposed scheme achieves high efficiency of spectrum usage even with the presence of severe user collusion.

We study the impact of the new cooperative communications paradigm on the routing problem in wireless sensor networks. We consider the minimum-power routing problem with desired Quality of Service (QoS). The QoS, characterized by the end-to-end probability of success and bandwidth efficiency, represents the reliability and capability of the route. We propose a routing metric, which considers the merits of the cooperative communications to obtain the required transmitted power in order to achieve certain QoS. Since the minimum-power routing problem is an NP-complete problem, we propose simple heuristic routing algorithms, namely, Minimum Power Cooperative Routing (MPCR) and Cooperation Along the Shortest Non-Cooperative Path (CASNCP) algorithms, which require less power compared to the conventional shortest-path routing algorithms. The numerical results indicate that the proposed algorithms reduce the required power by up to 21% compared to the conventional shortest-path routing algorithms.

We present forensic issues related to image source coding, including the detection of blocking artifacts, detection of transform method, quantization step estimation, and PSNR estimation. In performing forensic analysis, we can achieve many objectives such as quality assurance of transmitted multimedia, rate control, signal restoration, security and authentication, and patent enforcement. This talk focuses on parameter estimation, using JPEG and SPIHT as example source coders. For JPEG, our system almost always accurately estimates the quantization table without error, and estimates the PSNR to within an error of 0.92 dB. An analytical formulation for SPIHT PSNR estimation employing the Cauchy distribution is also discussed. Combining results, we create a system which identifies what source coder was used to encode an image, along with the coding parameters.

The study of Joint Source-Channel Coding bit rate allocation faces the challenge of obtaining a close form solution for the function that links end-to-end distortion with channel signal-to-noise ratio when considering non-capacity achieving source and channel codes. In this talk, we start by addressing this problem by characterizing the Distortion-SNR (D-SNR) curve through a representation that uses a set of carefully selected points. I will show that the D-SNR can be closely approximated through a linear function in log-log scales and we discuss the implications of this result. Next, we use this approach to study the tradeoffs between Joint Source-Channel Coding bit rate allocation and the use of user cooperation. In the talk, I will focus on studying the effects that the source-channel-cooperation tradeoffs have on the D-SNR performance of different schemes and how this translates into conditions where use of cooperation present an advantage or not.

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A belief-assisted dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double-auction rules. Moreover, considering the budget constraints of the unlicensed users, a dynamic programming approach is further developed to optimize the spectrum allocation over time. The simulation results show that our proposed scheme not only approaches optimal outcomes with low overhead compared to general continuous double auction mechanisms, but also fully exploits the time diversity of spectrum resources when budget constraints exist.

In April 2002, the U.S. Federal Communications Commission (FCC) published a report and order that allows Ultra-WideBand (UWB) communication systems to be deployed on an unlicensed basis following Part 15 rules. The publication encourages researchers and scientists to devote their time and resources to the development of the UWB transmission technology. Due to its large transmission bandwidth, the UWB transmission technology promises to fulfill the demand of high transmission data rates and is considered as one of the transmission technologies in the coming fourth generation (4G) of wireless transmission. In this thesis, we follow the standard proposal IEEE 802.15.3a to implement the multiband OFDM UWB system in C programming language. After that, we analyze the system performance in the multipath channel, the IEEE 802.15.3a channel standard. Four different scenarios relating to the imperfection of frequency and timing synchronization are considered. The analysis is performed in two stages. First, we consider the performance of only the OFDM system. Degradation ratio and average bit error probability are the two metrics used to evaluate the performance. Secondly, we provide the way to obtain the performance bound of the entire MB-OFDM UWB system. The performance analysis provides us a good understanding of the system behavior in the IEEE 802.15.3a channel standard under various synchronization conditions. The knowledge obtained from the performance analysis would help improving the MB-OFDM UWB system in future, and that is our main contribution to the area of wireless communications.

Differential modulation is widely known as a practical alternative that provides a good tradeoff between receiver complexity and performance. However, the available differential schemes for wireless relay networks require perfect synchronization and/or provide limited transmission rates. This paper proposes a threshold-based differential decode-and-forward cooperative scheme that not only alleviates the problems of synchronization and rate limitation, but also efficiently exploits the cooperative relay channels via the use of a pre-determined decision threshold. In the proposed scheme, the source information is forwarded by the relay only if it is correctly decoded. The properly-designed threshold enables the destination to decide whether the received signal from the relay contains information such that the received signals from the source and the relay can be efficiently combined and jointly decoded. The bit error rate (BER) performance analysis of the proposed scheme is analyzed in case of differential M-ary PSK signals. A tight BER approximation is established, and BER upper bound and lower bound are determined. Based on the tight BER approximation, joint optimum decision threshold and power allocation are numerically evaluated. Both analytical and simulation results reveal that the decision threshold and the power allocation depend on qualities of the communication channels. Interestingly, when the link quality between relay and destination is very good, the effect of the threshold dominates the effect of the power allocation at high signal-to-noise ratio. For example, in case of differential QPSK signals with equal power allocation, the proposed scheme with a properly-designed threshold leads to more than 5 dB performance improvement over the scheme without the threshold at a BER of 104. When the transmitted power is allocated optimally, the performance is further improved by 0.5 dB at the same BER. Extensive simulation results are provided to validate the merit of the proposed scheme and confirm the theoretical analysis.

Radiation therapy treatment (i.e. Gamma Knife) is a kind of non-invasive, painless, bloodless surgery. During the treatment, hunderds of low energy radiation beams are focused on the tumors (or unwanted tissues), to kill them. Before the surgery, one important thing is to know exactly the position, size and shape of the tumor, through some medical imaging techniques. This is easy when the tumor is standing still, not moving at all. However, when the tumor is located in the chest, because of the breathing, the tumor is moving all the time. Ignoring the movement will cause lots of artifacts in the estimation of the tumor's geometry. In this talk, I will present the full story and present a method about how to deal with the movement.

In this talk, we propose a Stackelberg game theoretic framework for distributive resource allocation over multiuser cooperative communication networks to improve the system performance and stimulate cooperation. Two questions of who should relay and how much power for relaying are answered, by employing a two-level game to jointly consider the benefits of source nodes as buyers and relay nodes as sellers in cooperative communication. From the derived results, the proposed game not only helps the source smartly find relays at relatively better locations but also helps the competing relays ask reasonable prices to maximize their own utilities. From the simulation results, the relays in good locations or good channel conditions can play more important roles in increasing source node's utility, so the source would like to buy power from these preferred relays. On the other hand, because of competition from other relays and selections from the source, the relays have to set the proper prices to attract the source's buying so as to optimize their utility values.

In autonomous mobile ad hoc networks, nodes belong to different authorities and pursue different goals, therefore cooperation among them cannot be taken for granted. Meanwhile, some nodes may be malicious whose objective is to damage the network. In this talk I will present a joint analysis of cooperation stimulation and security in autonomous mobile ad hoc networks under a game theoretic framework. After that, I will present the progress of our sensor network and collaborative communication testbed implementation.

In today's groupmeeting, I will continue talking about the "Cognitive based Cooperative Multiple-Access" protocol I proposed last summer. The work is almost complete now and I have proven rigorously the results I conjectured before regarding the stability region. Moreover, I included a delay-analysis for the two-user symmetric case which is, beside queue stability, another very important performance measure for a network. I also included a comparison to conventional cooperative transmission and some ideas for future work.

Digital fingerprinting uniquely labels each distributed copy with user's ID and provides a proactive means to track the distributionof multimedia. Multi-user collusion is a powerful attack against digital fingerprinting, in which a group of attackers collectively mount attacks to remove the embedded identification information. To resist such multi-user collusion and support multimedia forensics, we investigate the side information based multimedia fingerprinting. We explore techniques to utilize side information of collusion attacks during colluder identification process, and show that the means of the detection statistics at the detector's side can significantly improve the traitor tracing capability. We also investigate how the fingerprint detector can probe such side information from the colluded copy, and our simulation results show that the proposed scheme helps the fingerprint detector achieve the optimum detection performance.

In this talk, we consider the design of distributed space-time codes for wireless networks. Distributed space-time coding (DSTC) can be achieved through node cooperation to emulate multiple transmit antennas. We derive the distributed space-time codes design criteria for different scenarios based on the pairwise error probability (PEP) analysis. First, we consider the decode-and-forward protocol in which each relay node decodes the symbols that it receives from the source node before retransmission. We prove that space-time codes, designed to achieve full diversity and maximum coding gain in the MIMO channels, will achieve full diversity but not necessarily maximizing the coding gain if used with the decode-and-forward protocol. Next we consider the amplify-and-forward protocol in which each relay node does not decode the symbols but it can perform simple operations such as linear transformation of the received signals and then amplifies the signal before retransmission. We derive the space-time code design criteria for the amplify-and-forward protocol and prove that a space-time code designed to achieve full diversity and maximum coding gain in MIMO channels will achieve the same if used with the amplify-and-forward protocol.

Recent development in multimedia and network technologies has raised the critical issue of protecting multimedia content security and enforcing digital rights. Cryptographic tools (e.g., encryption and authentication) alone are not sufficient since the protection disappears after the data are delivered to users. To address the post-delivery protection, multimedia forensics combines digital domain evidence to determine whether multimedia content has been altered, to indicate how these alterations were made, and to identify who participated in the alterations.

This talk addresses several issues in multimedia forensics. First, multimedia fingerprinting for traitor tracing will be presented. Then, the dynamics among users in the forensic systems and the behavior forensics will be formulated and analyzed. Finally, the impact of forensic tools on current multimedia communication frameworks will be investigated, and secure fingerprint multicast schemes will be presented, which collectively address the security and the bandwidth efficiency of networked multimedia.

Wireless networking and resource allocation are general strategies to utilize the limited wireless radio resources, control the co-channel interferences, and enhance the network performances. To reduce the overhead imposed by such strategies, the mobiles of the next generation networks have their own autonomies for resource allocation in a distributive way. However, the non-cooperative competition of the radio resources results in low system efficiency. So how to ensure cooperation among autonomous users is one of the most important wireless networking research topics. There are many types of approaches to enforcing cooperation such as incentive based, referee based, punishment based, collaborative communication based, etc. In this talk, we concentrate on one of the approaches and employ it to OFDMA networks.

For incentive based approach, we propose bargaining method to have mutual benefits. Specifically, a fair and simple scheme to allocate subcarrier, rate, and power for multiuser single cell OFDMA systems is considered. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach proposes the fairness and low complexity implementation based on Nash Bargaining Solutions and Coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between both users. Based on this algorithm, we develop a multiuser bargaining algorithm where optimal coalition pairs among users are constructed. The simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than those of the scheme with max-min fairness.

We also briefly mention the other approaches. For referee based approach, we propose non-cooperative game approach with a referee for multi-cell OFDMA networks. Collaborative communication based approach and punishment based approach are also briefly discussed to give an overview on how to cooperate in wireless networks.

Identification of genes expressed in a cell-cycle-specific periodical manner is of great interest to understand cyclic systems which play a critical role in many biological processes. However, identification of cell-cycle regulated genes by raw microarray gene expression data directly is complicated by the factor of synchronization loss, thus remains a challenging problem. Decomposing the expression measurements and extracting synchronized expression will allow to better represent the single-cell behavior and improve the accuracy in identifying periodically expressed genes. In our study, we propose a resynchronization-based algorithm for identifying cell-cycle-related genes. We introduce a synchronization loss model by modeling the gene expression measurements as a superposition of different cell populations growing at different rates. The underlying expression profile is then reconstructed through resynchronization and is further fitted to the measurements in order to identify periodically expressed genes. Results from both simulations and real mircorarray data will be showed.

mPCA stands for mixture principle component analysis. It combines a probabilistic formulation to PCA, makes it a mixture model and brings in the Bayesian framework. mPCA can be used as a classification tool, both for supervised and unsupervised learning. In our study, we use mPCA as an unsupervised clustering tool and apply it in PET parametric imaging. Through mPCA, we segmented the PET image into different parts, each corresponds to tissues with different properties. I’ll explain what is the “different properties?during the talk.

In autonomous mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. In this talk, we focus on cooperation enforcement in autonomous mobile ad hoc networks under noisy and imperfect observations and study the basic packet-forwarding function using the repeated game models with imperfect information. Two approaches have been proposed to obtain cooperation-enforcement strategies based solely on each node's own past actions and its private imperfect observation of other nodes' information: belief-based packet forwarding framework and review-based packet forwarding framework. As for the belief-based approach, we not only show that the proposed strategy with belief system can achieve sequential equilibrium but also establish its performance bounds. The simulation results illustrate that the proposed belief-based packet forwarding approach can enforce the cooperation with only a small performance degradation compared to the unconditionally cooperative outcomes. As for the review-based strategy, we show that this approach is able to approach the unconditional cooperative outcomes by using large-enough review length. Simulation results match our theoretical derivation.

We consider the outage probability analysis of multi-node amplify-and-forward relay network with N relay nodes helping the source. We consider a system in which each relay node amplifies the source signal only. We obtain an approximation for the outage probability which is tight at high signal-to-noise ratio (SNR). This tight outage approximation shows that the system can achieve a maximum diversity of order N+1. For the case of N=1, our approach gives the same result obtained previously by Laneman et. al. for the single relay scenario.

We consider the design of distributed diagonal space-time codes (DDSTC) for N relay nodes helping the source. We impose the diagonal structure of the code to simplify synchronization between the different relay nodes because it is very difficult to synchronize simultaneous transmissions of randomly distributed relay nodes. We derive an upper bound on the outage probability of the system, which shows that a diversity of order N can be achieved. Then, we derive the code design criterion for the DDSTC based on minimizing the pairwise error probability (PEP). It turns out that the code design criterion is to maximize the minimum product distance, which is the same criterion used for designing diagonal algebraic space-time (DAST) codes and designing full-rate full-diversity space frequency (SF) codes.

In typical sensor network deployment, some nodes may be more important than other nodes because the death of these nodes cause the network disintegration. The network disintegration causes early termination of information delivery. To overcome this problem, we propose a class of routing algorithms called keep connect algorithms, that explicitly consider the connectivity of the network while making the routing decision. The algorithm can be used along with any existing routing algorithms. When doing the routing decision, the keep connect algorithm embeds the importance of the nodes in the routing cost. The importance of a node is quantified by the connectivity of the remaining network when that particular node dies. In particular, we propose two criteria for describing the connectivity of the remaining network. First, the importance of a node is quantified by how severe the remaining network becomes disconnected/disintegrated when that particular node dies. Second, the connectivity of the remaining network is quantified by the Fiedler value of the graph when that particular node is removed. The proposed algorithm achieves on average 20 ~ 50% better network lifetime and total delivered packets when it is used on top of MTE algorithm. The proposed algorithm also achieves around 20% improvement compared to the flow augmentation algorithm. We also outline the distributed implementation of our proposed algorithm. The MTE based distributed implementation achieves more than 2 times more total delivered packets before the network becomes disconnected, compared to flow augmentation based algorithm.

We study the impact of cooperative routing for maximizing the network lifetime in sensor network applications. We propose a joint cooperative transmission and energy aware routing algorithm to prolong the network lifetime. In contrast to the previous works, our approach uses the maximum lifetime power allocation, instead of minimum power allocation. Using the maximum lifetime power allocation, the cooperative nodes allocate their transmit power according to the channel condition and the residual energy in the nodes. Our maximum lifetime cooperative routing scheme combines the maximum lifetime power allocation and the energy aware routing to maximize the network lifetime. We demonstrate that our proposed solution achieves 1 to 3.5 and 1 to 2 times longer network lifetime and total delivered packet compared to noncooperative routing, when it is used with MTE and FA algorithms, respectively. Furthermore, the maximum lifetime power allocation achieves 1 to 2 times longer lifetime, compared to maximum power allocation in MTE and FA routing schemes. We also provide distributed implementation of the proposed algorithm.

In this work, a new multiple access approach is proposed that takes into account the broadcast nature of the wireless channel. The new approach employs a relay to boost the system throughput. This approach is based on a new idea in which the relay utilizes the empty time slots available in a TDMA frame. The relay stores the packets that failed transmissions in previous time slots. At each time slot, the relay listens to the channel and retransmits the packet at the head of its queue if the channel is free. This will better utilize the channel resources and will introduce on-demand spatial diversity into the network. Two different protocols are proposed to implement this new multiple-access scheme. The stability criteria of the associated queueing systems are studied and analytical expressions for the maximum stable throughput are provided for the symmetrical users case. Numerical results indicate a significant increase in the maximum stable throughput by using the new multiple-access protocol over pure TDMA.

In this paper, we propose a new cooperative communication protocol which achieves higher data rate while keeping the same diversity order as that of the conventional cooperative schemes. The proposed scheme considers relay selection via the available partial channel state information (CSI) at the source and the relays. In this work, we discuss the single and multi relay-selection decode-and-forward cooperative scenarios.

In the single-relay scenario, we determine when the source needs to cooperate with the relay, i.e., ``When to cooperate?''. We prove that full diversity order is achieved and show that the data rate is significantly increased. Furthermore, we derive an approximate expression of the achievable data rate and an upper bound on the symbol error rate (SER) performance for M-PSK signalling.

In the multi-node scenario, where arbitrary N relays are available, the source determines when it needs to cooperate with one relay only, and which relay to cooperate with, i.e., ``When to cooperate?'' and ``Whom to cooperate with?''. We show that full diversity is guaranteed and that a significant increase of the data rate is achieved. For the symmetric scenario, we derive an approximated data rate expression and obtain an upper bound on the SER performance. Moreover, we present the tradeoff between the achievable data rate and the corresponding SER. Finally, the obtained analytical results are verified through computer simulations.

Cooperative diversity exploits the broadcast nature of wireless channels by allowing users to relay information for each other so as to create multiple signal paths. In this talk I will discuss what is the best strategy from the viewpoint of a resource allocation protocol, to match source coding with cooperation diversity for conversational multimedia communications by studying the distortion performance for different schemes. I will present results that show that the best performance is obtained when all layers of a layered-coded source are sent with user cooperation (using decode-and-forward in most cases) if the source-destination channel is bad, and with no user cooperation, if the source-destination channel is good. The results also show that the gains from cooperative diversity outweigh the loss due to the sacrifice in overall bandwidth and that cooperation performance is sensitive to the proportion of communication capacity allocated for cooperation.

Extending network lifetime is considered as an energy efficient technique that enable extensive uses of powerful data gathering capability of wireless sensor network (WSN). However, most of existing works aims to increase network lifetime through the designs of efficient algorithms or the designs of energy efficient sensors, but leaves cooperation among sensors unexplored. In this paper, cooperative sensor protocol and relay deployment in WSN is proposed to improve the network lifetime. First, cooperative transmission is employed among sensor nodes. With an objective of maximizing the network lifetime under a constraint on bit-error-rate performance, we determine which sensors should cooperate and how much power to allocate for cooperation. A closed form solution is provided for a two-sensor WSN. Based on the obtained two-sensor solution, a fast suboptimal algorithm is developed for multiple sensor case. Moreover, the network lifetime is further improved by deploying additional relays with high energy to help all sensors transmit their information. The network lifetime is maximized by choosing the optimum location for each relay and optimally allocating the power that the relay helps each sensor. A suboptimal algorithm is proposed for the WSN with multiple relays. Simulation results show that the network lifetime of the proposed WSN with cooperative sensor employment improves 3 times compared with the non-cooperative WSN. In addition, deploying a cooperative relay in the proper location leads to up to 3.25 times longer network lifetime than that of the non-cooperative WSN when the energies of the relay and sensors are equal. The network lifetime increases upto 12 times longer when the relay has energy 10 times higher than that of sensors.

Due to limitation on transmitted power level, any UWB system faces major design challenges in achieving wide coverage while assuring an adequate system performance. In this paper, an employment of cooperative communications in UWB is proposed to enhance UWB system performance by exploiting the broadcasting nature of wireless channels and the cooperation among UWB devices. Symbol-error-rate (SER) performance analysis and optimum power allocation are provided for cooperative UWB multiband OFDM systems with decode-and-forward cooperative protocol. To capture the multipath-clustering phenomenon of UWB channels, the SER performance is characterized in terms of cluster and ray arrival rates. An optimum power allocation is determined based on two different objectives, namely minimizing the overall transmitted power and maximizing the system coverage. Furthermore, an improved cooperative UWB multiband OFDM scheme is proposed to take advantage of unoccupied subbands. Simulation results are shown to validate the theoretical analysis.

In this paper, we propose an OFDM cooperative protocol that not only achieves full diversity but also efficiently utilizes available bandwidth. The proposed protocol exploits limited feedback from the destination terminal (central node) such that each relay is able to help forward information of multiple sources in one OFDM symbol. To specify how relay-source pairs should be assigned, we propose two practical relay-assignment schemes, including fixed-location scheme in which the relays are fixed at optimum locations, and centralized-control scheme in which the relays are assigned by the central node. We provide outage probability analysis of the proposed protocol in wireless indoor environment. Moreover, a lower bound on the outage probability of any relay-assignment schemes is established, and the performance of the proposed relay-assignment schemes is analyzed. We also investigate the application of the proposed protocol to enhance the performance of UWB systems. In UWB wireless indoor scenarios, both theoretical and simulation results show that the proposed cooperative protocol can achieve 75% power saving and 200% coverage extension compared to the non-cooperative UWB system proposed in the IEEE 802.15.3a standard.

In autonomous ad hoc networks, nodes belong to different authorities and pursue different goals, therefore cooperation among them cannot be taken for granted. On the contrary, to maximize their own benefits, nodes may tend to be selfish. Furthermore, some nodes may be malicious, whose objective is to cause damage to the network. In this paper we formally analyze the cooperation and security in autonomous ad hoc networks under a game theoretical framework. When analyzing the cooperation strategies, besides Nash equilibrium, other optimality criteria, such as Pareto optimality, subgame perfection, fairness, cheat-proofing, and noise resistance, have also been considered. We first study a simple yet illuminating two-player packet forwarding game, and conclude that a necessary condition for a strategy to be optimal from a selfish node's point of view is not to help its opponent more than its opponent has helped him. The obtained results are then extended to the multi-player packet forwarding game, both noiseless and noisy situations have been studied and the optimal strategies are proposed. Furthermore, malicious behaviors have also been investigated, and the optimal strategies are studied under different situations. The analysis shows that when the proposed strategies are used by all the selfish nodes in the network, the damage that can be caused by attackers is bounded as well as very limited. More surprisingly, our results show the presence of attackers may even help improving the network performance.

In autonomous mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. In this paper, we focus on cooperation enforcement in the autonomous mobile ad hoc networks with noise and imperfect observation and study the basic packet-forwarding function using the repeated game models with imperfect information. A belief-based packet forwarding framework is proposed to obtain cooperation-enforcement strategies solely based on each node's own past actions and his imperfect observation of other nodes' information. More importantly, the proposed strategy with belief system can not only achieve sequential equilibrium of the packet-forwarding game but also approach the optimal cooperation payoffs for two-player and multi-player cases. The simulation results illustrate that the proposed belief-based packet forwarding approach achieves near-optimal performance in the ad hoc networks with noise and imperfect observation.

To reduce the bandwidth for watermark distribution, multicast is used as an alternative to unicast. We exploit the fact that, when employing spread-spectrum embedding upon a transformed image or video, there exist some coefficients that are more suited for watermark embedding than others. Only these coefficients should be watermarked and distributed separately. Unfortunately, this distribution scheme has many assumptions that include error-free transmission, spatial resolution, frame rate, etc. In the presence of a heterogeneous network where users require different levels of quality, we require a scalable video coding method. In this presentation, we will explore how watermarking can be used in conjunction with a scalable video codec. In particular, we discuss problems regarding video communication such as error protection and bandwidth efficiency, along with security issues such as watermark robustness and the embedding process.

Recent development in multimedia processing and network technologies has raised the critical issue of protecting multimedia content security and enforcing digital rights. Cryptographic tools (e.g., encryption and authentication) alone are not sufficient since the protection disappears after the data are delivered to users. To address the post-delivery protection, multimedia fingerprinting is an emerging technology to identify users who have legitimate access to the plaintext content but use it for unintended purposes. It provides a proactive means to trace the illegal usage of multimedia by inserting unique identification information ("fingerprint") into the content before distribution.

However, the uniqueness of each distributed copy poses new challenges to multimedia fingerprinting. The global nature of Internet enables a group of attackers to collectively mount attacks and effectively remove traces of the identifying fingerprints. Such a multi-user collusion attack poses serious threats to multimedia forensics. Digital fingerprints should resist multi-user collusion as well as attacks by a single adversary. Furthermore, for networked video applications with a large number of users, enabling traitor tracing and employing digital fingerprinting technology complicate the secure and efficient distribution of multimedia. This comes from the fact that traditional multicast technology cannot be directly applied to fingerprinted multimedia since different users receive slightly different copies. Therefore, in networked multimedia applications, it is critical to collectively address the security and the bandwidth efficiency and design secure fingerprint multicast schemes.

This talk addresses various issues in digital fingerprinting and discusses recent advances in traitor tracing for multimedia forensics. Traitor tracing using multimedia fingerprinting will be presented, including the investigation of multi-user collusion and collusion resistance of multimedia fingerprinting. In addition, the dynamics of the multimedia forensic system and behavior forensics in multimedia fingerprinting will be formulated and analyzed. Finally, secure fingerprint multicast schemes will be presented, which securely and efficiently distribute fingerprinted multimedia over networks.

In cooperative ad hoc networks, nodes usually belong to same authorities and pursue common goals. Since nodes in such networks will usually unconditionally help others, without necessary countermeasures, they are extremely vulnerable to inside attacks. In this paper we investigated how to secure cooperative ad hoc networks against inside attacks in a game theoretic framework. We focused on the most basic networking function, namely packet forwarding, and modeled the interactions between good nodes and inside attackers as secure packet forwarding games. The worst case scenario was studied where good nodes have no prior knowledge of the other nodes' types while inside attackers can know the types of all the other nodes. The Nash equilibrium strategies for the secure packet forwarding games under noiseless environment were first proposed. Then, the effects of noise on packet forwarding strategy design were investigated, and the Nash equilibrium strategies for the secure packet forwarding games under noisy environment were also proposed. Both analysis and simulation show that when the proposed strategies are adopted by good nodes, the damage that can be caused by the inside attackers is bounded as well as limited, and the performance of good nodes can be guaranteed.

One of the most relevant questions in implementing cooperative diversity protocols is how relay-source pairs should be assigned. In this paper, we address this problem and propose practical protocols for relay-assignment in cooperative wireless networks. We also investigate the application of the proposed protocols in coverage area extension in wireless networks. Outage probability is provided as a performance measure for the proposed protocols. First, we derive the performance of a hypothetical Genie-Aided protocol that provides an upper bound on the performance of any relay-assignment algorithm. This hypothetical protocol assumes that there is a Genie that, for each source node, places a relay at the optimal location to help that source. Then we describe and analyze the performance of two practical algorithms: the base-station/access-point (BS/AP) controlled protocol, and the Nearest-Neighbor protocol. The BS/AP-controlled protocol can be implemented at the BS or the AP, and it tries to emulate the Genie-Aided protocol. The second protocol, Nearest-neighbor, is a simple distributed protocol, in which the assigned relay is chosen to be the node between the user and the BS/AP such that it is the nearest neighbor to the user. We provide outage probability analysis for all the proposed protocols, and our analytical results are validated via computer experiments. Simulation results for two communication setups are considered: rural scenarios for cellular systems, and indoor scenarios for wireless local area networks (WLAN). By utilizing the proposed protocols, simulation results indicate a signicant gain in coverage area over the direct transmission scheme. For the rural cellular system case, coverage extension of about 250% can be achieved by the BS/AP-controlled protocol. For the indoor WLAN, a 350% increase in the coverage area can be achieved by both the BS/AP-controlled and Nearest-neighbor protocols, as both protocols provide comparable performance in the indoor WLAN scenario.

This talk will briefly outline several open problems that we are addressing at BYU, in an effort to find areas of common interest with CSPL. The topics to be discussed include: (1) time-of-arrival estimation for MIMO-OFDM channel estimation, (2) semi-blind uplink source separation using constant-modulus signals, (3) sensor deployment for source localization and tracking, (4) resource allocation for downlink spatial multiplexing, (5) MIMO channel prediction, and (6) scheduling in multi-antenna ad hoc networks.

The design objective in wireless network scheduling algorithms is to guarantee Quality of Service (QoS) for each mobile user in a resource-shared environment and meanwhile maximize the total system throughput. Based on the Effective Capacity (EC) link model, we introduced a notion of delay-bound violation/tolerance probability as a QoS measure. Then Maximum Utility Scheduling (MUS) scheme is proposed, which jointly considers throughput maximization and QoS support. Basically, the approach has two major steps: First, select a user that has the maximum utility. Second, recursively estimate the EC link model functions and update corresponding QoS parameters in the utility function. Simulation results demonstrate that even under heavy network loads our proposed scheme can tolerate delay of service with a higher probability than other scheduling algorithms and achieve high throughput. Moreover, system overall performance can be optimized by properly choosing some parameter.

We all know that due to some communication and computation constraint, the multimedia offers different resolution. So the fingerpringting should also have this scalibility to handle this situation. And during collusion, the colluders may have different resolution copies, to achieve fairness, the colluders assume that the detector detect based on the whole sequence, but what will happen if this assumption fail? In today's meeting, I'll present the statistics if the detecor detect layer-by-layer, and what will the colluders do to attain their fairness.

We are already familiar with some optimization methods such as steepest decent, Newton methods, conjugate gradient, and so on. These methods all belong to single search strategy. Basically, we stick to one guess (potential solution) and try to improve it iteratively. However, these method may not work well when there are multiple local solutions. Evolutionary programming (EP) adpots a different strategy. It works with multiple "guesses". In each iteration of EP, there are a population of potential solutions. And these potential solutions interact in a way that mimics the nature (evolution, animal's social system). The basic idea is to "let the nature find its way". EP is a stochastic strategy that ENCOURAGES all potential solutions to move toward better places. And this kind of methods is able to deal with problems with multiple local optimals. After introducing EP, I'll talk about its application in PET imaging. In PET imaging treatment, the patient's blood sample is tested from time to time. This measurement is called "input function", which it quite painful and risky. However, we found that this measurement is not necessary, and we are able to estimate it. In this talk, I will formulate the estimation as a minimization problem, and try to solve it with an evolutionary programming method called Particle Swarm Optimation. And let's see how intelligent swarms could be.

In the future wireless communications, high speed data transmission services are highly demanded. Several schemes have recently been proposed for realizing such demands, such as Space-Time (ST) coded MIMO systems and Space- Frequency (SF) coded MIMO-OFDM systems. However, by given a current technology of wireless communications, equipping multiple antennas at the receiver or transmitter seems to be far from realistic. One mean of implementing the MIMO systems is to employ a concept of distributed antenna systems, namely cooperative communications. In this talk, I will present an efficient protocol for cooperative communications, namely a minimum SER selection adaptive protocol that exploits an upper bound on SER as a performance-comparing threshold for optimally choosing a modulation constellation and cooperative partners. Our proposed protocol also employs an adaptive modulation for maintaining a fixed bandwidth efficiency constraint. In addition, an optimum power allocation is also addressed in this study. Extensive computer simulations for evaluating the performance of the proposed protocol are provided. By given the fixed bandwidth efficiency and power constraints, our proposed protocol performs the best in comparison to such fixed protocols. Furthermore, it has been shown in the simulation results that the optimum power allocation scheme is superior to the equal power allocation scheme, in which the SNR difference is about 0.65 dB at SER of 10^-5. Although the proposed protocol is suboptimal in low SNR regimes, it has also been shown in the simulation results that it works remarkably well in all SNR levels, where it achieves the minimum SER through out the SNR range.

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) is one of a prominent communication system for realizing high speed data transmission services. One critical issue for such systems employing coherent receivers is channel estimation. Since the multipath delay profile of channels is arbitrary in the MIMO-OFDM systems, an effective channel estimator is needed to estimate such channels. In this paper, we first develop a pilot-embedded data-bearing approach for joint channel estimation and data detection, in which pilot-embedded data-bearing (PEDB) least-square (LS) channel estimation and maximum-likelihood (ML) data detection are employed. Then we propose an LS FFT-based channel estimator by employing the concept of FFT-based channel estimation to improve the PEDB- LS channel estimation via choosing certain significant taps in constructing a channel frequency response. The effects of model mismatch error inherently in the proposed LS FFT-based channel estimator when considering non-integer multipath delay profiles, and its performance analysis are investigated. Under the framework of pilot embedding, we further propose an adaptive LS FFT-based channel estimator that employs the optimum number of taps such that an average total energy of the channels dissipating in each tap is completely captured in order to compensate the model mismatch error as well as minimize the corresponding noise effect to improve the performance of the LS FFT-based channel estimator. Simulation results reveal that the adaptive LS FFT-based channel estimator is superior to the LS FFT-based and PEDB-LS channel estimators under quasi-static channels or low Doppler's shift regimes.

In autonomous mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other or, honestly revealing its private information, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by awarding some payment for cooperative behaviors. In this talk, we model the pricing and routing as multi-stage dynamic games. By taking into consideration that the packet-forwarding will incur a cost to the relay user and the successful transmission brings benefits to the sender/receiver, we propose a dynamic pricing framework to maximize the sender/receiver's payoff by considering the dynamic nature of MANETs, meanwhile, keeping the forwarding incentives of the relay nodes by providing the optimal payments based on the auction rules. The contributions of this paper are multi-folds: Firstly, by modeling the pricing and routing as a dynamic game, the sender is able to exploit the time diversity in MANET to increase their payoffs by adaptively allocating the packets to be transmitted into different stages. Secondly, based on the auction structure and routing dynamics, a simple optimal dynamic programming algorithm is developed to implement efficient multi-stage pricing for autonomous MANETs. Thirdly, the path diversity of MANET is exploited using the optimal auction mechanism in each stage. The simulation results illustrate that the proposed dynamic pricing framework has significant performance gains over the static pricing algorithms.

In this talk, we propose a new cooperative protocol, which takes into consideration the channel state information (CSI) available at the source. With such protocol, a significant improvement in the transmission rate can be achieved in decode-and-forward cooperative transmission. Closed-form expressions for the transmission rate and the symbol error rate (SER) are derived for both M-PSK and M-QAM signalling. Moreover, two optimization metrics are considered in the protocol design to enhance the system performance, the first is based on minimizing the SER alone, while the second is based on minimizing a joint function of both the SER and the transmission rate. Finally, the obtained analytical results are verified through computer simulations.

Ultra-wideband (UWB) has emerged as a technology that offers great promises to satisfy the growing demand for low cost and high-speed digital wireless home networks. In our group meeting today, I would like to present my work on the baseband implementation of UWB system employing multiband OFDM that has been proposed in the IEEE 802.15.3a standard. Basically, the transceiver comprises of data scrambler, convolutional en/decoder, bit-interleaver, constellation mapping, and IFFT/FFT. In the talk, I will describe these components in detail.

Symbol-error-rate (SER) performance analysis is provided for the decode-and-forward space time block coded cooperation protocol. We derive the SER for the case of two relays forwarding the source data and emulating the Alamouti scheme. The analysis presented can be easily generalized to any number of relays emulating orthogonal space-time block code. We derive closed-form SER expressions for both the M-PSK and M-QAM signals. Moreover, a SER bound is established which is tight at high signal-to-noise ratio. Based on this tight bound, we also determine the optimum power allocation for this space-time block coded cooperative network. Simulations are used to validate the theoretical results. Next, we will present two schemes for the multi-node amplify and forward collaborative networks. In the first scheme, each relay only amplifies the signal it receives from the source. We denote this system as the 2 phase system. In the second scheme, each relay applies maximum ratio combining (MRC) on the signals from the source and all previous relays. We denote this system as the MRC based system. We provide an SER bound for the 2 phase system. The analysis of the MRC system is intractable so we prove via simulations that it does not offer any improvement over the 2 phase system due to the noise propagation problem. We then provide a Lower bound on the SER performance of any amplify and forward system. We then prove that the 2 phase system achieves this bound if the relays are close to the source.

In wireless ad hoc networks, autonomous nodes would be reluctant to forward others' packets because of the nodes' limited energy. However, such selfishness would deteriorate both the system efficiency and users' performances. Hence, it is crucial to design a distributed mechanism for enforcing the cooperation among greedy users for packet forwarding. Moreover, having only with the local information, the optimal cooperation is not known to distributed users/nodes, even though they are willing to cooperate. In this paper, we proposed a self-learning repeated game framework to study how to cooperate and maintain the cooperation among selfish nodes. The framework has two major schemes: First, an adaptive repeated game scheme ensures the cooperation among users for the current cooperative packet forwarding probabilities. The repeated game scheme provides the users with a mechanism that any deviating user would be punished enough by others in the future, so that no user has incentive to deviate. Second, a self-learning scheme tries to find the better cooperation probabilities that are feasible and benefit all users. Starting from noncooperation, the above two proposed schemes are applied iteratively, so that better cooperation is discovered and maintained in each iteration. From the simulation results, the proposed framework achieves solutions within up to 4% compared to the solution of a centralized system. Moreover, the proposed algorithm is able to enforce cooperation among selfish nodes.

We propose a differential transmission scheme for amplify-and-forward protocol in a two-user cooperative communications system. By efficiently combining signals from both direct and relay links, the proposed scheme provides superior performance to those of direct transmissions without relay in either differential detection or coherent detection. While the exact BER formulation of the proposed scheme is not available currently, we provide, as a performance benchmark, an exact bit error rate (BER) formulation for a case of optimumcombining cooperation system with M-ary differential phase shift keying signals. We also provide BER upper bound and lower bound as well as their simple approximations, in which one of them is tight at high signal-to-noise ratio (SNR). In addition, the optimum power allocation for the cooperation system is determined based on the provided BER formulations. We show that the proposed differential cooperative transmission scheme together with the optimum power allocation yields comparable performance to the optimum-combining scheme. Simulation result show that a significant performance improvement is obtained for a case of optimum power allocation strategy comparing to the performance with equal power allocation scheme.

In this talk, we provide performance analysis for UWB systems that successfully captures the unique multipath-rich property and multipath-clustering phenomenon of UWB channels. Using the Saleh-Valenzuela model, we characterize pairwise error probability (PEP) and outage probability for UWB systems employing multiband OFDM based on the cluster arrival rate, the ray arrival rate within a cluster, and the cluster and ray decay factors. Furthermore, an approximation technique is established, which allows us to obtain closed-form performance formulations that provide insightful understanding of the effect of channel characteristics on the performances of UWB systems. Finally, we characterize the effect of random-clustering phenomenon on the performance of UWB-MIMO systems. The theoretical results reveal that regardless of the clustering behavior of UWB channels, the diversity gain can be improved by increasing the number of jointly encoded subcarriers, the number of jointly encoded OFDM symbols, or the number of antennas. The coding gain on the other hand, depends heavily on the cluster-arriving channels. Extensive simulation results are provided to support the theoretical analysis.

Source coding diversity produces multiple independent source descriptions so as to improve the received quality. Cooperative diversity exploits the broadcast nature of wireless networks by allowing multiple users to relay information for each other, so as to create multiple signal paths. In this talk, I will discuss what is the best strategy in combining these two types of diversity for multimedia communications. We study the distortion-rate performance for different joint diversity schemes. Our results show that exploring both types of diversity improves the system performance most, but in most of cases, only one type of diversity can achieve most of the diversity gain. The best performance is obtained when the mobile can switch between cooperative and non-cooperative operation depending on the channel conditions. Thus, it is important to design efficient protocols that manage this switch and provides motivation for all users to cooperate.

Digital fingerprinting can be used to identify the source of illicit copies of multimedia data and enforce digital rights. Collusion involves multiple adversaries to collectively mount attacks against digital fingerprints and is a cost-effective method to undermine the traitor tracing capability. In this talk, we study the dynamics among attackers during collusion and consider the problem of traitors within traitors, in which some selfish colluders wish to minimize their own risk of being caught while still profiting from collusion. In particular, we investigate the strategy that selfish colluders can use to minimize their probability of being detected and analyze its performance.

Wireless networking and resource allocation are general strategies to utilize the limited wireless radio resources, control the co-channel interferences, and enhance the network performances. To reduce the overhead imposed by such strategies, the mobiles of the next generation networks have their own autonomies for resource allocation in a distributive way. However, the non-cooperative competition of the radio resources results in low system efficiency. So how to ensure cooperation among autonomous users is one of the most important wireless networking research topics. There are many types of approaches to enforcing cooperation such as incentive based, referee based, punishment based, collaborative communication based, etc. In this talk, we concentrate on the first two approaches and employ them to OFDMA networks.

For incentive based approach, we propose bargaining method to have mutual benefits. Specifically, a fair and simple scheme to allocate subcarrier, rate, and power for multiuser single cell OFDMA systems is considered. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach proposes the fairness and low complexity implementation based on Nash Bargaining Solutions and Coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between both users. Based on this algorithm, we develop a multiuser bargaining algorithm where optimal coalition pairs among users are constructed. The simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than those of the scheme with max-min fairness.

For referee based approach, we propose non-cooperative game approach with a referee for multi-cell OFDMA networks. The goal is to minimize the overall transmitted power under the constraints that each user has the desired throughput and each user's power is bounded. The pure non-cooperative game may have some undesired Nash Equilibriums with low performances. To improve the performances, a referee is introduced to the networks and is in charge of monitoring the outcome of non-cooperative competition of resources for the distributed users. If the outcome is not desired, some users should be kicked out from using the resources such as sub-channels or the required transmission rates should be reduced, so that the rest of users can share the resources more efficiently. From the simulation results, the proposed scheme reduces the overall transmitted power greatly compared with the fixed channel assignment algorithm and pure water-filling algorithm.

Collaborative communication based approach and punishment based approach are also briefly discussed to give an overview on how to cooperate in wireless networks.

The talk has two parts: In the first part, I will give a brief introduction on the system vulnerability of wireless ad hoc networks: attacks, protection, and security analysis. In the second part, I will focus on securing cooperative ad hoc networks against inside attacks.