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The demodulation of M-PSK and M-QAM signals using particle filtering

In this paper, the problem of particle filter to demodulate uncoded M-PSK and M-QAM signals over Rayleigh flat fading channels is investigated. Based on the Jakes' model, the channel state is modelled as a first order autoregressive (AR) process. The observation noise is assumed complex Gaussian. It is shown that, in the demodulation of uncoded PSK signals, particle filter doesn't have superiority compared to the decision-directed Kalman filter due to the M-ary phase ambiguity of the PSK signals, but it is not the case to detect uncoded QAM signals. As can be seen, while using the same pilot symbol rate in the demodulation of uncoded M-QAM signals particle filter outperforms the decision-directed Kalman filter and it performs well even in the low pilot symbol rate.