Particle filters for demodulation of M-ary modulated signals in noisy fading communication channels
We address the problem of demodulation of M-ary modulated signals under conditions of noisy fading channels. The transmitted signal is corrupted in a random manner by a variety of possible mechanisms, and our aim is to recover the original message from the observations. This is a challenging non-linear filtering problem, and in order to solve it an efficient simulation-based algorithm, based on particle filters, is developed. The method combines sequential importance sampling, a selection scheme, Markov chain Monte Carlo (MCMC) methods and variance reduction techniques. Optimal fixed-lag smoothing is also considered. An application to the problem of demodulation of digital M-ary differential phase shift keyed (MDPSK) signals is presented and an extensive simulation study is carried out. The results show that the algorithm outperforms the current methods that are routinely used in most communication applications.