Cognitive backoff mechanism for IEEE802.11ax high-efficiency WLANs

Abstract

Carrier sense multiple access with collision avoidance(CSMA/CA) in current IEEE 802.11 wireless local area networks (WLANs) uses a uniformly distributed binary exponential backoff (BEB) mechanism that is mainly based upon exponential increases of the contention window (CW) to avoid repeated collisions. After each consecutive collision, the CW is doubled until it reaches the maximum value. Under dense conditions, however, the blind selection of the CW greatly reduces throughput, whereas under sparse conditions with smaller number of contending stations, the blind exponential increase of the CW for collision avoidance causes unnecessarily long delays. Therefore, it fails to achieve high efficiency in both dense and sparse environments with the current BEB mechanism. In this paper, we propose a cognitive backoff (CB) mechanism that adaptively determines the CW to provide efficient collision avoidance with high throughput and low delay under both dense and sparse conditions. In the proposed CB mechanism, the measured conditional collision probability and the number of backoff stages determine the CW. A performance analysis with an event-driven simulator, NS3, reveals that the proposed CB can achieve higher throughput and lower delay than the BEB, without much implementation complexity while preserving fairness.