Distributed MAC Strategy for Exploiting Multi-user Diversity in Multi-rate IEEE 802.11 Wireless LANs

TL;DR

This paper introduces R-DCF, a distributed MAC protocol that enhances multi-user diversity and throughput in multi-rate IEEE 802.11 WLANs by prioritizing high-rate users and reducing collisions.

Contribution

The paper proposes R-DCF, a novel distributed MAC strategy that exploits multi-user diversity and channel conditions to improve throughput in multi-rate WLANs.

Findings

R-DCF significantly increases throughput compared to legacy MAC.

Analytical model accurately predicts R-DCF performance.

Offline adaptive backoff achieves near-optimal throughput.

Abstract

Fast rate adaptation has been established as an effective way to improve the PHY-layer raw date rate of wireless networks. However, within the current IEEE 802.11 legacy, MAC-layer throughput is dominated by users with the lowest data rates, resulting in underutilization of bandwidth. In this paper, we propose and analyze a novel distributed MAC strategy, referred to as Rate-aware DCF (R-DCF), to leverage the potential of rate adaptation in IEEE 802.11 WLANs. The key feature of R-DCF is that by introducing different mini slots according to the instantaneous channel conditions, only contending stations with the highest data rate can access the channel. In this way, the R-DCF protocol not only exploits multi-user diversity in a fully distributed manner but also reduces the loss of throughput due to collisions. Through analysis, we develop an analytical model to derive the throughput of R-DCF in general multi-rate WLANs. Using the analytical model we investigate the performance of R-DCF protocol in various network settings with different rate adaptation strategies and channel variations. Based on the analysis, we further derive the maximal throughput achievable by R-DCF. For practical implementation, an offline adaptive backoff method is developed to achieve a close-to-optimal performance at low runtime complexity. The superiority of R-DCF is proven via extensive analyses and simulations.