K. J. Ray Liu

Cooperative Communication Protocols in Wireless Networks: Performance Analysis and Optimum Power Allocation

In this paper, symbol-error-rate (SER) performance analysis and optimum power allocation are provided for uncoded cooperative communications in wireless networks with either decode-and-forward (DF) or amplify-and-forward (AF) cooperation protocol, in which source and relay send information to destination through orthogonal channels. In case of the DF cooperation systems, closed-form SER formulation is provided for uncoded cooperation systems with PSK and QAM signals. Moreover, an SER upper bound as well as an approximation are established to show the asymptotic performance of the DF cooperation systems, where the SER approximation is asymptotically tight at high signal-to-noise ratio (SNR). Based on the asymptotically tight SER approximation, an optimum power allocation is determined for the DF cooperation systems. In case of the AF cooperation systems, we obtain at first a simple closed-form moment generating function (MGF) expression for the harmonic mean to avoid the hypergeometric functions as commonly used in the literature. By taking advantage of the simple MGF expression, we obtain a closed-form SER performance analysis for the AF cooperation systems with PSK and QAM signals. Moreover, an SER approximation is also established which is asymptotically tight at high SNR. Based on the asymptotically tight SER approximation, an optimum power allocation is determined for the AF cooperation systems. In both the DF and AF cooperation systems, it turns out that an equal power strategy is good, but in general not optimum in cooperative communications. The optimum power allocation depends on the channel link quality. An interesting result is that in case that all channel links are available, the optimum power allocation does not depend on the direct link between source and destination, it depends only on the channel links related to the relay. Finally, we compare the performance of the cooperation systems with either DF or AF protocol. It is shown that the performance of a systems with the DF cooperation protocol is better than that with the AF protocol. However, the performance gain varies with different modulation types and channel conditions, and the gain is limited. For example, in case of BPSK modulation, the performance gain cannot be larger than 2.4 dB; and for QPSK modulation, it cannot be larger than 1.2 dB. Extensive simulation results are provided to validate the theoretical analysis.

A Distributed Relay-Assignment Algorithm for Cooperative Communications in Wireless Networks

A crucial challenge in the implementation of a cooperative diversity protocol is how to assign source-relay pairs. In this paper, we address this problem under the knowledge of the users spatial distribution and we propose a distributed relay-assignment algorithm for cooperative communications. In the proposed algorithm, the relay is chosen to be the nearestneighbor to the user towards the base-station (access-point). An outage analysis for the proposed scheme is provided under a random spatial distribution for the users, and an approximate expression for the outage probability is derived. Simulation results for indoor wireless local area networks (WLAN) are provided. By utilizing the proposed protocol, simulation results indicate a significant gain in coverage area over the direct transmission scheme under fairly the same bandwidth efficiency and fixed average transmitted power. A 350% increase in the coverage area can be achieved by the distributed Nearest-neighbor protocols. This coverage increase can also be translated to energy efficiency over direct transmission when fixing the total coverage area.

Game theoretical mechanism design methods

Dynamic spectrum access with cognitive radios has become a promising approach to improve spectrum efficiency by adaptively coordinating different users access according to spectrum dynamics. However, selfish users competing with each other for spectrum may exchange false private information or collude with others to get more access to the spectrum and achieve higher profits. In this article, we investigate two game-theoretical mechanism design methods to suppress cheating and collusion behavior of selfish users: a self-enforcing truth-telling mechanism for unlicensed spectrum sharing and a collusion-resistant multistage dynamic spectrum pricing game for licensed spectrum sharing.

Cognitive Radio Networking and Security: A Game-Theoretic View

Description: With the rapid growth of new wireless devices and applications over the past decade, the demand for wireless radio spectrum is increasing relentlessly. The development of cognitive radio networking provides a framework for making the best possible use of limited spectrum resources, and it is revolutionising the telecommunications industry. This book presents the fundamentals of designing, implementing, and deploying cognitive radio communication and networking systems. Uniquely, it focuses on game theory and its applications to various aspects of cognitive networking. It covers in detail the core aspects of cognitive radio, including cooperation, situational awareness, learning, and security mechanisms and strategies. In addition, it provides novel, state-of-the-art concepts and recent results. This is an ideal reference for researchers, students and professionals in industry who need to learn the applications of game theory to cognitive networking.

Evolutionary Game Framework for Behavior Dynamics in Cooperative Spectrum Sensing

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.

Collaborative Multiple-Access Protocols for Wireless Networks

In this paper, 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 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.

Behavior Dynamics in Media-Sharing Social Networks

In large-scale media-sharing social networks, where millions of users create, share, link, and reuse media content, there are clear challenges in protecting content security and intellectual property, and in designing scalable and reliable networks capable of handling high levels of traffic. This comprehensive resource demonstrates how game theory can be used to model user dynamics and optimize design of media-sharing networks. It reviews the fundamental methodologies used to model and analyze human behavior, using examples from realworld multimedia social networks. With a thorough investigation of the impact of human factors on multimedia system design, this accessible book shows how an understanding of human behavior can be used to improve system performance. Bringing together mathematical tools and engineering concepts with ideas from sociology and human behavior analysis, this one-stop guide will enable researchers to explore this emerging field further and ultimately design media-sharing systems with more efficient, secure, and personalized services.

Scalable multimedia fingerprinting forensics with side information

Digital fingerprinting uniquely labels each distributed copy with users ID and provides a proactive means to track the distribution of 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, this paper investigates 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 detectors 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.

A game theoretical approach for image denoising

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 Steins 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 Steins estimate while incurring a cost of increasing the minimum of the true MSE. We also propose a heuristically distributed approach for coalition formation. 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.

Impact of Social Network Structure on Multimedia Fingerprinting Misbehavior Detection and Identification

Users in video-sharing social networks actively interact with each other, and it is of critical importance to model user behavior and analyze the impact of human factors on video sharing systems. In video-sharing social networks, users have access to extra resources from their peers, and they also contribute their own resources to help others. Each user wants to maximize his/her own payoff, and they negotiate with each other to achieve fairness and address this conflict. However, some selfish users may cheat to their peers and manipulate the system to maximize their own payoffs, and cheat prevention is a critical requirement in many social networks to stimulate user cooperation. It is of ample importance to design monitoring mechanisms to detect and identify misbehaving users, and to design cheat-proof cooperation stimulation strategies. Using video fingerprinting as an example, this paper analyzes the complex dynamics among colluders during multiuser collusion, and explores possible monitoring mechanisms to detect and identify misbehaving colluders in multiuser collusion. We consider two types of colluder networks: one has a centralized structure with a trusted ringleader, and the other is a distributed peer-structured network. We investigate the impact of network structures on misbehavior detection and identification, propose different selfish colluder identification schemes for different colluder networks, and analyze their performance. We show that the proposed schemes can accurately identify selfish colluders without falsely accusing others even under attacks. We also evaluate their robustness against framing attacks and quantify the maximum number of framing colluders that they can resist.