Analysis of Exponential Backoff with Multipacket Reception in Wireless Networks

A collision resolution scheme is essential to the performance of a random-access wireless network. Most schemes employ exponential backoff (EB) to adjust the transmission attempt rate according to the changing traffic intensity. Previous work on exponential backoff was mostly based on the conventional single-packet-reception model where no more than one packet can be successfully received at any one time. In this paper, we analyze the performance of EB based on a multi-packet reception (MPR) model, in which multiple packets can be received successfully at once (i.e., collisions do not occur unless the number of packets transmitted exceeds a threshold that is more than 1). Using a Markov chain model, we derive the throughput expressions for both carrier-sensing and non-carrier-sensing networks with MPR capability under the saturated-traffic condition. We find that the two systems share a number of common performance results. In particular, the state of both systems can be characterized by the same Markov-chain model. The binary exponential backoff (BEB), in which the backoff factor r is set to 2, does not yield the optimum network throughput in both cases. In addition, in both cases, the asymptotic collision probability goes to 1/r and the maximum asymptotic throughput increases roughly linearly with M when the population size approaches infinity. We show how to adjust r to achieve the best throughput performance. Our results show that the optimal r that maximizes the asymptotic throughput increases with M for non-carrier-sensing systems and BEB is close to optimal for carrier-sensing systems. Simulation results validate the accuracy of our theoretical analysis