Weighted Max-Min Resource Allocation for Frequency Selective Channels

In this paper, we discuss the computation of weighted max-min rate allocation using joint TDM/FDM strategies under a PSD mask constraint. We show that the weighted max-min solution allocates the rates according to a predetermined rate ratio defined by the weights, a fact that is very valuable for telecommunication service providers. Furthermore, we show that the problem can be efficiently solved using linear programming. We also discuss the resource allocation problem in the mixed services scenario where certain users have a required rate, while the others have flexible rate requirements. The solution is relevant to many communication systems that are limited by a power spectral density mask constraint such as WiMax, Wi-Fi and UWB

Coordination and Bargaining over the Gaussian Interference Channel

This work considers coordination and bargaining between two selfish users over a Gaussian interference channel using game theory. The usual information theoretic approach assumes full cooperation among users for codebook and rate selection. In the scenario investigated here, each selfish user is willing to coordinate its actions only when an incentive exists and benefits of cooperation are fairly allocated. To improve communication rates, the two users are allowed to negotiate for the use of a simple Han-Kobayashi type scheme with fixed power split and conditions for which users have incentives to cooperate are identified. The Nash bargaining solution (NBS) is used as a tool to get fair information rates. The operating point is obtained as a result of an optimization problem and compared with a TDM-based one in the literature.Comment: 5 pages, 4 figures, to appear in Proceedings of IEEE ISIT201

Alternating-Offer Bargaining Games over the Gaussian Interference Channel

This paper tackles the problem of how two selfish users jointly determine the operating point in the achievable rate region of a two-user Gaussian interference channel through bargaining. In previous work, incentive conditions for two users to cooperate using a simple version of Han-Kobayashi scheme was studied and the Nash bargaining solution (NBS) was used to obtain a fair operating point. Here a noncooperative bargaining game of alternating offers is adopted to model the bargaining process and rates resulting from the equilibrium outcome are analyzed. In particular, it is shown that the operating point resulting from the formulated bargaining game depends on the cost of delay in bargaining and how bargaining proceeds. If the associated bargaining problem is regular, a unique perfect equilibrium exists and lies on the individual rational efficient frontier of the achievable rate region. Besides, the equilibrium outcome approaches the NBS if the bargaining costs of both users are negligible.Comment: 8 pages, 6 figures, to appear in Proceedings of Forty-Eighth Annual Allerton Conference on Communication, Control, and Computin

Worst-Case Mahler Measure in Polytopic Uncertain Systems

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Competitive Spectrum Management with Incomplete Information

This paper studies an interference interaction (game) between selfish and independent wireless communication systems in the same frequency band. Each system (player) has incomplete information about the other player's channel conditions. A trivial Nash equilibrium point in this game is where players mutually full spread (FS) their transmit spectrum and interfere with each other. This point may lead to poor spectrum utilization from a global network point of view and even for each user individually. In this paper, we provide a closed form expression for a non pure-FS epsilon-Nash equilibrium point; i.e., an equilibrium point where players choose FDM for some channel realizations and FS for the others. We show that operating in this non pure-FS epsilon-Nash equilibrium point increases each user's throughput and therefore improves the spectrum utilization, and demonstrate that this performance gain can be substantial. Finally, important insights are provided into the behaviour of selfish and rational wireless users as a function of the channel parameters such as fading probabilities, the interference-to-signal ratio

Compensation-based Game for Spectrum Sharing in the Gaussian Interference Channel

This paper considers an optimization problem of sum-rate in the Gaussian frequency-selective channel. We construct a competitive game with an asymptotically optimal compensation to approximate the optimization problem of sum-rate. Once the game achieves the Nash equilibrium, all users in the game will operate at the optimal sum-rate boundary. The contributions of this paper are twofold. On the one hand, a distributed power allocation algorithm called iterative multiple waterlevels water-filling algorithm is proposed to efficiently achieve the Nash equilibrium of the game. On the other hand, we derive some sufficient conditions on the convergence of iterative multiple waterlevels water-filling algorithm in this paper. Through simulation, the proposed algorithm has a significant improvement of the performance over iterative water filling algorithm and achieves the close-to-optimal performance