Adaptive Rate Selection Scheme Based on Intelligent Learning Algorithm in Wireless LANs

摘要

Although IEEE 802.11 wireless local area networks (WLANs) physical layers (PHYs) support multiple transmission rates, it not specifies how and when to switch between the permitted rates. In this paper, a novel method is introduced for rate selection in IEEE 802.11 WLANs by proposing an intelligent learning algorithm, which is simply based on local acknowledgement frames to indicate the correct reception of the packet. Based on the intelligent learning algorithm, a rate selection scheme is also proposed, which aims to improve the system throughput by adapting the transmission rate to the current link condition. Numerical and simulation results show that the proposed intelligent learning . Algorithm is convergent quickly, and the rate selection scheme is closely approximates the ideal case with the perfect knowledge about the channel, which significantly improves quality of service (QoS) in terms of throughput and delay metrics.