Markov characterization of channels with soft decision outputs

It is shown that a methodology based on hidden Markov models is applicable to the modeling of slowly varying Rayleigh fading channels with additive Gaussian noise and soft decision outputs. The fading is considered to be frequency nonselective, and ideal demodulation is considered throughout. To prove the validity of robustness of the modeling technique, various results that show good agreement between the simulated channels and the models found are presented. Two soft decision statistical distributions, namely, the soft burst and soft burst interval distributions, are defined and compared. To illustrate the accuracy of the models obtained, the simulation and model outputs are compared for a convolutional encoder with Viterbi decoding and various degrees of interleaving.<
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