a model for comparing rate adaptation algorithms
Rate adaptation algorithms are critical to improving the throughput performance of WLANs. While previous studies have examined the performance of different algorithms in some detail using numerous measurements and simulations, there is a lack of a theory that would allow comparison across different channel conditions. This paper is a first step towards developing an abstract model that can allow us to (a) estimate or predict the performance of different algorithms and (b) allow us to make general statements about which algorithms would perform better, under what channel conditions. Our work is empirical in nature and uses three rate algorithms available in the Madwifi driver to examine the problem. We identify two key metrics, the speed of adaptation and the quality of adaptation, that taken together nicely encapsulate an algorithm's performance. We then show how these metrics predict the throughput behavior of the three rate algorithms considered with an accuracy of over 70\%. Furthermore, we show that these metrics can be used to make very general statements comparing the behavior of any pair of algorithms over a wide range of channels.
rate adaptation madwifi wireless protocol 802.11