A Semi Markov-based Analysis of Rate Adaptation Algorithms in Wireless LANs

Rate adaptation plays a key role in determining the performance of wireless LANs. In this paper, we introduce a semi-Markovian framework to analyze the performance of two of the most popular rate adaptation algorithms used in wireless LANs, namely automatic rate fallback (ARF) and adaptive automatic rate fallback (AARF). Given our modeling assumptions, the analysis is exact and provides closed form expressions for the achievable throughput of ARF and AARF. We illustrate the benefit of our analysis by numerically comparing the throughput performance of ARF and AARF in two different channel regimes. The results show that neither of these algorithms consistently outperforms the other. We thus propose and analyze a new variant to AARF, called persistent AARF (or PAARF), and show that it achieves a good compromise between the two algorithms, often performing close to the best algorithm in each of the studied regimes.