Efficient method of M-PSK demodulation based on particle filtering
An efficient particle filtering algorithm for demodulation of M-PSK signals at the background of non-Gaussian noise is proposed. The state-space model of the observation signal is formulated including the dynamics of channel parameters' updating. The resulting estimation of informative symbols and channel parameters is done in two parallel contours. The simulations for QPSK signals have shown that for a sufficiently high number of particles the proposed method outperforms classical demodulation approach based on Gardner and Costas loops.