Evolutionary Games for Multiple Access Control: From Egoism to Altruism

International audienceThis paper studies multiple access games within a large population of mobiles decomposed into several groups. Mobiles interfere with each other through many local interactions. We assume that each mobile (or player) cooperates with its group by taking into account the performance of its group. We parameterize the degree of cooperation which allows to cover the fully non-cooperative behavior, the fully cooperative behavior, and even more, the fully altruistic behavior, all these as special cases of this parameters choice. In this context, we model and study such cases using the theory of evolutionary games which extend to cover this kind of behavior. We define and characterize the equilibrium (called Evolutionary Stable Strategy) for these games and establish the optimal level of cooperation that maximizes the probability of successful transmission and present some optimization issues. We also study the game dynamics both in its classical form and in presence of delays

Evolutionary Games for Multiple Access Control

ISBN : 978-0-8176-8354-2In this paper, we formulate an evolutionary multiple access control game with continuous-variable actions and coupled constraints. We characterize equilibria of the game and show that the pure equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionarily stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics, such as Brown-von Neumann-Nash dynamics, Smith dynamics, and replicator dynamics. In addition, we examine correlated equilibrium for the single-receiver model. Correlated strategies are based on signaling structures before making decisions on rates. We then focus on evolutionary games for hybrid additive white Gaussian noise multiple-access channel with multiple users and multiple receivers, where each user chooses a rate and splits it over the receivers. Users have coupled constraints determined by the capacity regions. Building upon the static game, we formulate a system of hybrid evolutionary game dynamics using G-function dynamics and Smith dynamics on rate control and channel selection, respectively. We show that the evolving game has an equilibrium and illustrate these dynamics with numerical examples