Toward History-Aware Robust 802.11 Rate Adaptation

Abstract

Rate adaptation is a mechanism unspecified by the IEEE 802.11 standards, yet critical to the system performance by exploiting the multirate capability at the physical layer. In this paper, we conduct a systematic experimental study on rate adaptation over 802.11 wireless networks. Our key contributions are as follows: First, we present a critique on popular design guidelines adopted by many practical algorithms and we uncover their limitations. Our study reveals that these seemingly correct guidelines can be misleading in practice, thus incurring significant performance penalty in certain scenarios. Second, we study the short-term channel dynamics and explore how they guide rate adaptation. To this end, we design and implement a new History-Aware Robust Rate Adaptation Algorithm (HA-RRAA). HA-RRAA uses short-term loss ratio to opportunistically guide its rate change decisions, a cost-effective adaptive RTS filter to prevent collision losses from triggering rate decrease and an adaptive time window to limit transmissions at high loss rates. Our extensive experiments show that HA-RRAA outperforms popular algorithms in all tested scenarios, with goodput gains up to 51.9 percent in field trials.