Opportunistic Random Access with Temporal Fairness in Wireless Networks

User diversity arises when wireless users experience diverse channel conditions. This paper proposes three opportunistic random access algorithms that favor users with the best channel conditions in channel access. These algorithms operate on the contention mechanism of CSMA/CA and compute the contention window based on channel conditions. In one algorithm, the contention windows of all users share the same lower bound of zero. In another, the contention windows of users with different channel conditions are segmented without overlapping. The third algorithm adopts a normal distribution to select the backoff value in the contention window. These algorithms are also enhanced to provide temporal fairness and avoid starving the users with poor conditions. We implemented a Linux-based testbed for a real world performance evaluation and also developed the algorithms into the NS3 simulator to conduct comprehensive and controllable experiments. Extensive evaluations show that the proposed opportunistic access can significantly improve the network performance in throughput, delay and jitter over the current default CSMA/CA method.