EM-based ML channel estimation in OFDM systems with phase distortion using RB-EKF

• Published in: 2014 International Symposium on Wireless Personal Multimedia Communications (WPMC) pp. 232 - 237
• Main Authors: Carvajal, Rodrigo, Godoy, Boris I., Aguero, Juan C., Yuz, Juan I., Creixell, Werner
• Format: Conference Proceeding
• Language: English
• Published: National Institute of Information and Communicatio 01-09-2014
• Subjects: Channel estimation; Complexity theory; Estimation; Kalman filters; OFDM; Training; Vectors
• ISSN: 1347-6890
• DOI: 10.1109/WPMC.2014.7014822

In this paper we address the joint estimation of the channel impulse response in orthogonal frequency division multiplexing systems with phase distortion, namely phase noise and carrier frequency offset, phase noise bandwidth and the additive noise variance. The estimation algorithm is based on an implementation of the Extended Kalman Filter within the general framework of the Expectation-Maximization algorithm. We focus on the partial training case, where the transmitted signal is not fully known. To tackle this problem, we utilize a Rao-Blackwellized Extended Kalman Filter. We also compare our results with another nonlinear filtering technique, namely Rao-Blackwellized Particle Filtering, applied to this joint estimation problem. The performance of the two filtering techniques considered in this paper is evaluated in terms of the mean square error of the channel estimates and the numerical complexity introduced by each of these techniques.