Game-Theoretic Power Control for Interference Mitigation in Two-Tier Small Cell Networks

Abstract

Interference mitigation is a major challenge in deploying a two-tier small cell network, where small cells are deployed underlaying a central macrocell and share the same spectrum with the macrocell. In this paper, we develop a new decentralized power control solution for interference mitigation in a two-tier small cell network, from a game theoretic perspective. We aim to maximize the number of small cell user (SU) transmissions that can be admitted in the network while satisfying the signal-to- interference-noise ratio (SINR) constraints of both transmitting SUs and the macrocell user (MU). We formulate the problem of power control for SUs as a game with common utility. The Nash equilibria of the game are investigated. We then propose a learning automata based distributed discrete power control algorithm with which the SUs can learn from their action-reward histories and adjust their transmit powers towards a NE point. Simulation results show the proposed algorithm achieves higher number of SU transmissions that can be admitted compared with existing schemes in the literature.