Hidden Markov modeling of flat fading channels

Hidden Markov models (HMM's) are a powerful tool for modeling stochastic ra ndom processes. They are general enough to model with high accuracy a large variety of processes and are relatively simple allowing us to compute anal ytically many important parameters of the process which are very difficult to calculate for other models (such as complex Gaussian processes). Another advantage of using HMM's is the existence of powerful algorithms for fitti ng them to experimental data and approximating other processes, In this pap er, we demonstrate that communication channel fading can be accurately mode led by HMM's, and we find closed-form solutions for the probability distrib ution of fade duration and the number of level crossings.