Mean Field Energy Games in Wireless Networks

TL;DR

This paper applies mean field game theory to model and analyze energy-efficient distributed power control in large wireless networks, demonstrating potential energy savings at equilibrium.

Contribution

It introduces a novel application of mean field games to wireless power control, providing a framework for analyzing large systems with energy and channel state dynamics.

Findings

Mean field game approach improves energy efficiency.

Numerical results show significant gains.

Framework applicable to large wireless networks.

Abstract

This work tackles the problem of energy-efficient distributed power control in wireless networks with a large number of transmitters. The problem is modeled by a dynamic game. Each transmitter-receiver communication is characterized by a state given by the available energy and/or the individual channel state and whose evolution is governed by certain dynamics. Since equilibrium analysis in such a (stochastic) game is generally difficult and even impossible, the problem is approximated by exploiting the large system assumption. Under an appropriate exchangeability assumption, the corresponding mean field game is well defined and studied in detail for special cases. The main contribution of this work is to show how mean field games can be applied to the problem under investigation and provide illustrative numerical results. Our results indicate that this approach can lead to significant gains in terms of energy-efficiency at the resulting equilibrium.