OFDM Channel Estimation by a Linear EM-Map Algorithm

OFDM systems traditionally perform channel coefficients estimation relying on known training sequences. However in wireless systems, performance and mobility can be further enhanced by operating semi-blind channel estimation refinement between reference symbols. A channel tracking method based on a MAP version of the expectation-maximization (EM) algorithm and on a block representation of channel variations has been proposed. It performs better than already existing recursive algorithms but have a quadratic complexity. In this paper, we propose a simplified MAP algorithm which has a linear complexity and we examine its convergence properties. This simplification is an adaptation of the one step late technique to the EM algorithm for MAP estimation. The proposed algorithm is applicable to both single carrier and OFDM systems. Simulations are presented in the context of 5 GHz WLANs, showing that this algorithm perform as well as the MAP version of the EM algorithm in the mobile environment, without any loss in performance in the static situation