MAC-layer interference mitigation in dynamic and distributed environment: dynamic graphic game with stochastic learning

In this paper, we investigate the problem of channel selection for MAC-layer interference mitigation in the dynamic and distributed environment, in which each user only has its local information, and each user is dynamically active due to its specific data service requirement. Accordingly, a dynamic interference graph is defined to capture the dynamic and local interaction. Based on the defined interference graph, the MAClayer interference mitigation problem is formulated as a dynamic graphic game. It is proved to be an exact potential game, in which the existence of the Nash equilibrium (NE) is guaranteed. Furthermore, we design a fully distributed, online adaptive, stochastic learning algorithm for the interference-mitigation channel selection, which converges to the NE of the formulated game. Finally, we conduct simulations to validate the effectiveness of the proposed algorithm for MAC-layer interference mitigation in the dynamic and distributed environment.