Bayesian Approach for the Estimation of Phase Noise in SC-FDE Schemes
A solution for the problem of estimating the PN (Phase Noise) from the observation of the channel output in burst communications is to establish a state-model for the PN and determine the a posteriori Probability Density Function (pdf) of the state conditioned on all measurement data, thus providing the means to compute an optimal estimate with respect to any criterion, e.g., Minimum Mean-Squared Error (MMSE). However, except in the Gaussian case, it is extremely difficult to determine and propagate this density function. As a result, and since the observation model of the PN is non-linear, the a posteriori pdf becomes non-Gaussian, and a sub-optimal solution for the problem must be found. In this paper, the authors approximate the non-Gaussian pdf by a weighted sum of Gaussians.