Socially Conscious Channel Selection in 802.11 WLANs for Coexistence in a Non-cooperative Environment

The increasing number of independent IEEE 802.11 WLANs owned and managed by autonomous users has led to increased interfer-ence, resulting in performance degradation and unfairness. Perfor-mance can be improved by allowing these networks to operate on different channels. Due to the autonomous nature of the networks, a suitable channel selection scheme should be distributed, adaptive and require no explicit coordination. In this paper, we model the channel selection of WLANs as a non-cooperative game in a learn-ing setting. Using a novel method of acquiring a disruption factor value, we propose a class of socially conscious channel selection schemes based on game-theoretic learning. These schemes are dis-tributed, adaptive and are able to improve fairness without explicit inter-network communication. These features allow the WLANs to coexist in an interference-limited but non-cooperative environment. They also have the advantage of not requiring any modification to the existing 802.11 standards. Simulations show improved fairness and aggregate throughput compared with two existing schemes