Distributed dynamic-TDD resource allocation in femtocell networks using evolutionary game

Abstract

Since uplink (UL) and downlink (DL) traffic loads are time-variant in femtocells, it is essential to adopt dynamic time-division duplexing (TDD) to effectively adjust the uplink and downlink transmission resources. However, the cross-link interference between dynamic TDD femtocells decreases the throughput gain of dynamic TDD. In this paper, we propose an evolutionary game-based distributed approach to choose the UL-DL configuration in order to minimize interference and maximize the system throughput in a large-scale femtocell network. A multiple populations evolutionary game is formulated to model femtocells with different traffic loads. We prove that the evolutionarily stable strategy (ESS) of the considered multiple populations evolutionary game is the optimal configuration which maximizes the system throughput. Simulation results confirm the effectiveness of the proposed evolutionary game-based approach for system throughput optimization in femtocells employing dynamic TDD.