SmartRate: A new dynamic rate adaptation algorithm for 802.11 wireless networks

Traditional rate adaptation algorithms (RAAs) suffer under congested scenarios as they are unable to differentiate between packet errors due to poor physical channel conditions, from those due to collisions arising from contention for the channel. This degrades the rate selection which results in a dramatic loss of throughput both for individual users and the system. This paper presents `SmartRate´, a throughput and packet size aware, passive measurement based, clientside RAA. It employs 802.11 MAC fragmentation for physical PER isolation, and employs a dynamic sampling regime to collect per-rate statistics. It uses a novel RSSI based volatility adaptivity mechanism to fine tune various parameters of the algorithm under different channel conditions (stationary or mobile). We compare SmartRate against SampleRate and AMRR in our wireless testbed and show that SmartRate outperforms them in single and multi-user cases.