| The design and analysis of wireless communication systems is very challenging because of the inherent instability of its medium: the propagation channels. In this thesis, we explore the usefulness of the Markov chain theory in the channel modeling and performance analysis of wireless communication systems. In particular, we first propose a hierarchical Markov model for the shadowed fading wireless channel. Then, with the help of Markov chain theory, we develop a unified analytical framework for the performance evaluation of switched diversity combining techniques which are the lowest complexity solution for fading mitigation. The proposed framework not only allows for the generalization of all previous analytical results in the literature, but also leads to a thorough comparison and tradeoff study of different switching strategies. In addition, starting from the traditional dual-branch switch and stay combining diversity techniques, we develop and analyze several switching-based diversity combining schemes. More specifically, we first generalize switched diversity to multi-branch scenario. Then, noting the deficiency of the pure switching-based combining schemes in taking advantage of available diversity paths, we further generalize them and propose two new low-complexity combining schemes for diversity-rich environments, namely generalized switch and examine combining (GSEC) and output-thresholded generalized selection combining (OT-GSC). In addition to their performance analysis, we make special effort to quantify the complexity savings of the proposed schemes with respect to the optimal ones. It is observed that comparing to the more popular selection-based combining schemes, switching-based combining schemes lead to simpler receiver structure, less signal processing, and lower power consumption at the cost of a certain performance loss. |
