An Adaptive Backoff Protocol with Markovian Contention Window Control

The backoff protocol is widely used for sharing a common channel among several stations in communication networks. The Binary Exponential Backoff (BEB) improves the system throughput but increases the capture effect, permitting a station to seize the channel for a long time. In this paper, we introduce and analyze a new class of adaptive backoff protocols where a station changes its contention window after a successful transmission differently than BEB. The transitions between the contention window states are determined by a stochastic matrix which describes a finite, irreducible, aperiodic Markov chain. We derive a stationary distribution of an associated embedded Markov chain in an explicit form and then find the stationary distribution of the basic Markov chain explicitly. Preliminary simulation results show that our backoff protocol can reduce the capture effect in Ethernet and wireless networks significantly.