On optimizing the backoff interval for random access schemes

To improve the channel throughput and the fairness of random access channels, we propose a new backoff algorithm, namely, Sensing Backoff Algorithm (SBA). A novel feature of the SBA scheme is the sensing mechanism, in which every node modifies its backoff interval according to the results of the sensed channel activities. In particular, every active node sensing the successful transmission decreases its backoff interval by an additive factor of the transmission time of a packet. In order to find the optimum parameters for the SBA scheme, we have studied the optimum backoff intervals as a function of different number of active nodes ( ) in a single transmission area with pure ALOHA type channels. We have found that the optimum backoff interval should be times the transmission time of a packet when the random access channel operates under a pure-ALOHA scheme. Based on this result, we have numerically calculated the optimum values of the parameters for SBA, which are independent of . The SBA scheme operates close to the optimum backoff interval. Furthermore, its operation does not depend on the knowledge of . The optimum backoff interval and the SBA scheme are also studied by simulative means. It is shown that the SBA scheme out-performs other backoff schemes, such BEB and MILD. As a point of reference, the SBA scheme offers a channel capacity of 0.19 when is 10, while the MILD scheme can only offer 0.125. The performance gain is about 50%.