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.

Current rate control (selection) algorithms in IEEE 802.11 are not based on accurate measurements of packet errors caused at the physical layer. Instead, algorithms act on measurements which, either implicitly or explicitly, mix physical errors with those arising from contention. In this paper we first illustrate how contention can adversely affect the performance of these algorithms, and point out the potential benefits of an ability to isolate physical packet error rate. We introduce and compare two variants of a single core idea enabling the isolation and accurate measurement of physical packet error, based on exploiting existing features of the MAC standard in a novel way. One is based on the RTS/CTS mechanism, and the other on packet fragmentation. Using proof of concept experimental results from a wireless testbed, we show these mechanisms can be used to improve the performance of two existing algorithms, SampleRate and AMRR, both for individual stations and for the system as a whole, and show how incremental deployment is unproblematic. We discuss how the methodology can be integrated in a modular way into rate control algorithms with acceptable overhead.

End to end available bandwidth is often constrained by IEEE 802.11 hops in the access network. Available bandwidth measurement is particularly challenging in the wireless environment because of adaptive data rates, a time varying channel, and CSMA/CA based contention instead of simple FIFO queueing. We present a novel estimation scheme for IEEE 802.11 networks in infrastructure mode, based on passive monitoring, without any need for access point cooperation or protocol modifications. We employ an empirical map of relationships local to the client station, and direct measurements of channel utilisation, combined with the known packet size dependent overheads. In testbed experiments we show how the method provides a reliable lower bound of the achievable IP bandwidth, which is also a good point estimate in the case where sources are not greedy. We compare against probegap, an alternative method which also measures channel utilisation, but does not take rate or PER into account.