A Markov Chain Approach to IEEE 802.11WLAN Performance Analysis

Wireless communication always attracts extensive research interest, as it is a core part of modern communication technology. During my PhD study, I have focused on two research areas of wireless communication: IEEE 802.11 network performance analysis, and wireless cooperative retransmission. The first part of this thesis focuses on IEEE 802.11 network performance analysis. Since IEEE 802.11 technology is the most popular wireless access technology, IEEE 802.11 network performance analysis is always an important research area. In this area, my work includes the development of three analytical models for various aspects of IEEE 802.11 network performance analysis. First, a two-dimensional Markov chain model is proposed for analysing the performance of IEEE 802.11e EDCA (Enhanced Distributed Channel Access). With this analytical model, the saturated throughput is obtained. Compared with the existing analytical models of EDCA, the proposed model includes more correct details of EDCA, and accordingly its results are more accurate. This better accuracy is also proved by the simulation study. Second, another two-dimensional Markov chain model is proposed for analysing the coexistence performance of IEEE 802.11 DCF (Distributed Coordination Function) and IEEE 802.11e EDCA wireless devices. The saturated throughput is obtained with the proposed analytical model. The simulation study verifies the proposed analytical model, and it shows that the channel access priority of DCF is similar to that of the best effort access category in EDCA in the coexistence environment. The final work in this area is a hierarchical Markov chain model for investigating the impact of data-rate switching on the performance of IEEE 802.11 DCF. With this analytical model,