A Game-Theoretic Approach to Exploit Partially Overlapping Channels in Dynamic and Distributed Networks

In this letter, we investigate the partially overlapping channels for interference mitigation in dynamic and distributed networks. The interference mitigation problem is formulated as a dynamic game, which is proved to be an exact potential game. Furthermore, the performance bounds of the Nash equilibrium (NE) are theoretically derived and analyzed. Finally, we design a fully distributed, stochastic learning algorithm to converge to the NE of the formulated game. Simulation results validate the effectiveness of the proposed algorithm.