Finite-state Markov models for correlated fading channels in wireless communications

Various types of diversity systems are used as countermeasures for fading in wireless communications. In most previous work, performance analyses for diversity systems assumes independent fading channels, and long-term averaging is carried out under perfect interleaving assumption. Performance of systems utilizing an ARQ scheme depends on the dynamics of fading channels, which is not captured in long-term averaging. Bit-level simulation of the performance can be very time consuming. In this dissertation, we design and build finite-state Markov models representing correlated Rayleigh fading channels under the scenarios of spatial diversity and frequency diversity. These models can provide both static and dynamic properties of correlated fading channels, and are very useful for the performance evaluation of diversity systems.; We develop and analyze a methodology to partition the equivalent received signal-to-noise ratio of a diversity system into a finite number of states, which correspond to different channel quality, based on level crossing theory and a time duration criterion for each state. Two popular diversity combining schemes i.e., maximal ratio combining and selection combining are considered in our models, and the worst case for the selection combining is considered as well. We present novel analyses and derivations for the level-crossing rate of the received SNR for different combining schemes under correlated fading channels. The physical models of correlated fading channels for spatial diversity and frequency diversity are studied, and provide justification for our level-crossing rate derivations. The efficacy of our models is verified by numerical calculations and computer simulations for different combining schemes and channel conditions. We consider two correlated equal-power fading channels, and extend our models to two correlated non-equal-power fading channels and to L (L > 2) uncorrelated equal power fading channels. These extensions broaden the applicability of our finite-state Markov models.; We demonstrate the usefulness of our Markov models by two examples. First, we obtain the long time average performance for diversity systems with different diversity combining schemes, and the results agree with what have been obtained by other approaches in literature. Second, we carry out performance analysis for diversity systems utilizing a hybrid ARQ scheme with rate-compatible punctured convolutional codes, showing analytical results that agree with simulations.