Modeling, capacity, and joint source/channel coding for Rayleigh fading channels

A finite-state Markov channel (FSMC) model for a Rayleigh fading channel (RFC) is constructed by partitioning the range of its received signal-to-noise ratio (SNR) into K intervals. The crossover probabilities of the K binary symmetric channels associated with its states are calculated. The second-order statistics of the received SNR are used to approximate the Markov transition probabilities. The capacity of the modeled channel can then be calculated with recursive algorithms. A joint source and channel coding scheme based on quantization for this channel model is studied. The decoder is assumed to have access to the channel state information, which it uses to adjust itself to varying channel conditions. It is shown that the use of the finite-state Markov channel model and knowledge of the channel state information significantly improves the performance of the system