Jamming energy allocation in training-based multiple access systems

We consider the problem of jamming attack in a multiple access channel with training-based transmission. First, we derive upper and lower bounds on the maximum achievable ergodic sum-rate which explicitly shows the impact of jamming during both the training phase and the data transmission phase. Then, from the jammer's design perspective, we analytically find the optimal jamming energy allocation between the two phases that minimizes the derived bounds on the ergodic sum-rate. Numerical results demonstrate that the obtained optimal jamming design reduces the ergodic sum-rate of the legitimate users considerably in comparison to fixed power jamming.The work of X. Zhou was supported by the Australian Research Council's Discovery Projects funding scheme (Project No. DP110102548)

Jamming Games in the MIMO Wiretap Channel With an Active Eavesdropper

This paper investigates reliable and covert transmission strategies in a multiple-input multiple-output (MIMO) wiretap channel with a transmitter, receiver and an adversarial wiretapper, each equipped with multiple antennas. In a departure from existing work, the wiretapper possesses a novel capability to act either as a passive eavesdropper or as an active jammer, under a half-duplex constraint. The transmitter therefore faces a choice between allocating all of its power for data, or broadcasting artificial interference along with the information signal in an attempt to jam the eavesdropper (assuming its instantaneous channel state is unknown). To examine the resulting trade-offs for the legitimate transmitter and the adversary, we model their interactions as a two-person zero-sum game with the ergodic MIMO secrecy rate as the payoff function. We first examine conditions for the existence of pure-strategy Nash equilibria (NE) and the structure of mixed-strategy NE for the strategic form of the game.We then derive equilibrium strategies for the extensive form of the game where players move sequentially under scenarios of perfect and imperfect information. Finally, numerical simulations are presented to examine the equilibrium outcomes of the various scenarios considered.Comment: 27 pages, 8 figures. To appear, IEEE Transactions on Signal Processin

Physical Layer Security Game: Interaction between Source, Eavesdropper and Friendly Jammer

Special issue on physical layer securityInternational audiencePhysical layer security is an emerging security area that explores possibilities of achieving perfect secrecy data transmission between the intended network nodes, while possible malicious nodes that eavesdrop the communication obtain zero information. The so-called secrecy capacity can be improved using friendly jammers that introduce extra interference to the eavesdroppers. Here, we investigate the interaction between the source that transmits the useful data and friendly jammers who assist the source by \masking" the eavesdropper. In order to obtain a distributed solution, one possibility is to introduce a game theoretic approach. The game is de¯ned such that the source pays the jammers to interfere the eavesdropper, therefore increasing the secrecy capacity. The friendly jammers charge the source with a certain price for the jamming and there is a tradeo® for the price. If the price is too low, the pro¯t of the jammers is low and if the price is too high, the source would not buy the \service" (jamming power) or would buy it from other jammers. To analyze the game outcome, we de¯ne and investigate a Stackelburg type of game and construct a distributed algorithm. Our analysis and simulation results show the e®ectiveness of friendly jamming and the tradeo® for setting the price. The distributed game solution is shown to have similar performances to those of the centralized one. This work was supported by NSF CNS-0831371, and was supported by the Research Council of Norway through the project entitled "Mobile-to-Mobile Communication Systems (M2M)"

Game Theory in Communications:a Study of Two Scenarios

Multi-user communication theory typically studies the fundamental limits of communication systems, and considers communication schemes that approach or even achieve these limits. The functioning of many such schemes assumes that users always cooperate, even when it is not in their own best interest. In practice, this assumption need not be fulfilled, as rational communication participants are often only interested in maximizing their own communication experience, and may behave in an undesirable manner from the system's point of view. Thus, communication systems may operate differently than intended if the behavior of individual participants is not taken into account. In this thesis, we study how users make decisions in wireless settings, by considering their preferences and how they interact with each other. We investigate whether the outcomes of their decisions are desirable, and, if not, what can be done to improve them. In particular, we focus on two related issues. The first is the decision-making of communication users in the absence of any central authority, which we consider in the context of the Gaussian multiple access channel. The second is the pricing of wireless resources, which we consider in the context of the competition of wireless service providers for users who are not contractually tied to any provider, but free to choose the one offering the best tradeoff of parameters. In the first part of the thesis, we model the interaction of self-interested users in a Gaussian multiple access channel using non-cooperative game theory. We demonstrate that the lack of infrastructure leads to an inefficient outcome for users who interact only once, specifically due to the lack of coordination between users. Using evolutionary game theory, we show that this inefficient outcome would also arise as a result of repeated interaction of many individuals over time. On the other hand, if the users correlate their decoding schedule with the outcome of some publicly observed (pseudo) random variable, the resulting outcome is efficient. This shows that sometimes it takes very little intervention on the part of the system planner to make sure that users choose a desirable operating point. In the second part of the thesis, we consider the competition of wireless service providers for users who are free to choose their service provider based on their channel parameters and the resource price. We model this situation as a two-stage game where the providers announce unit resource prices in the first stage and the users choose how much resource they want to purchase from each provider in the second stage. Under fairly general conditions, we show that the competitive interaction of users and providers results in socially optimal resource allocation. We also provide a decentralized primal-dual algorithm and prove its convergence to the socially optimal outcome