Particle Filtering for Iterative Data and Phase Estimation

In this paper we consider the iterative decoding of channels with strong phase noise. We propose to estimate the phase using a message passing algorithm based on particle filtering. Instead of estimating the phase directly we use the whole estimated probability density function for the channel decoder. Three versions of phase estimators are derived. The simulation results are given for binary LDPC codes. We compare the proposed iterative data and phase estimators with another solution where the forward backward algorithm is performed over the trellis obtained from the discretization of the phase. The results show that the proposed algorithm achieves a good compromise between performances and complexity