Semi-Markov process based model for performance analysis of wireless LANs

In this paper, we propose a new semi-Markov process based model to compute the network parameters such as saturation throughput, for the IEEE 802.11 Distributed Coordination Function (DCF) employing the Binary Exponential Backoff (BEB). The backoff stages of BEB and their backoff intervals are modeled as the states of semi-Markov process and their state holding-times, respectively. The proposed model is simpler than Bianchi´s two-dimensional Markov chain based model, with the number of states in the proposed model being of the order O(m), where m is the number of backoff stages in the BEB, compared with the Bianchi´s model where number of states is of the order O(2^m). Using the proposed semi-Markov process model, we compute the parameters of interest in wireless LANs, such as conditional collision probability, packet transmission probability, and saturation throughput. We show that the proposed model is quite accurate in computing these parameters of interest. Moreover, we show that the computation time with the proposed model is approximately one-tenth of that with Bianchi´s model, using Matlab simulations. Thus, the proposed model achieves accurate results with less complexity and computation time, and is suitable to be used for performance evaluation of complex protocols such as IEEE 802.11e.