Negotiation Strategies to Improve Distributed Power Allocation for Self-Organizing Heterogeneous Networks

As the traffic supported by wireless networks grows, new solutions to increase the throughput are emerging, such as heterogeneous networks, which face the challenge of self-organization in order to control the interference. A frequently used tool to model this problem is Game Theory, and we show that Communicate & Agree, a recent general-purpose negotiation-based algorithm for solving repeated games, can be applied to these network settings to provide Pareto-efficient results. As a particular application, we study a distributed power allocation problem, showing that Communicate & Agree provides better payoffs than a state-of-the-art baseline while being faster, thus making it an ideal candidate for self-organizing heterogeneous networks.