A hidden Markov model (HMM)-based MAP receiver for Nakagami fading channels

Signalling over Rayleigh fading channels can be classed as a general Gaussian problem. Optimal linear filtering can then be applied to jointly estimate the channel and detect the information sequence. For fading channels with non-Gaussian distributions, optimal linear filtering does not necessarily yield the best channel estimates. To exploit the channel memory, a first order finite Markov chain model (HMM) that statistically characterizes the Nakagami-m fading process is used to aid the channel estimation. Based on this, a maximum a posteriori (MAP) receiver using coherent detection is presented for binary PAM signals.