Joint Carrier Frequency Offset and Doubly Selective Channel Estimation for MIMO-OFDMA Uplink With Kalman and Particle Filtering

Abstract

This paper presents two novel approaches for joint carrier frequency offset (CFO) and doubly selective channel estimation in the uplink of multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) systems. Considering high-mobility situations, where channels change within one OFDMA symbol interval, and the time varying nature of CFOs, basis expansion modeling (BEM) is employed to represent the time variations of the channel. Two new approaches are then proposed based on Schmidt–Kalman filtering (SKF). The first approach utilizes Schmidt-extended Kalman filtering for each user to estimate CFO and BEM coefficients. The second approach uses Gaussian particle filtering along with SKF to estimate CFO and BEM coefficients of each user. The Bayesian Cramer–Rao bound is derived, and the performances of the new schemes are evaluated using the mean square errors. It is demonstrated that the new approaches can significantly improve the mean-square error performance in comparison with the existing methods.