Joint iterative detection and phase noise estimation algorithms using Kalman filtering

The problem of a slow varying phase noise (PN) estimation at a low signal to noise ratio (SNR) in a non-pilot aided receiver is considered. Two iterative algorithms using Kalman filtering are proposed to estimate the PN under the expectation-maximization (EM) framework. The first algorithm uses a soft decision directed extended Kalman smoother (EKS) to provide a suboptimal PN estimate. While the second algorithm overcomes the nonlinear structure of the EKS and improves the PN estimate by using a Kalman smoother (KS) which is applied assuming small PN values. An enhanced KS is proposed to maintain the KS performance in large PN values. Simulation results show that the performance of the proposed algorithms is close to the performance of the synchronized system with no PN effect.