Hidden Markov Modeling for Nakagami Fading Channel

In this paper, we proposed a novel hidden Markov model (HMM) to approximate the characteristic of the Nakagami Fading channel. Our study is based on a Hidden Markov Model (HMM). The channel switches between ‘good’ and ‘bad’ channel situation. The transition between the sub-states of the channel is governed by a Markov Chain, which some self-return state is hidden. The performance of the model is studied by simulating probability density functions (PDF), cumulative distribution functions (CDF), level cross rate (LCR) and average fade duration (AFD).