Expectation-Maximization (EM) Based Channel Estimation and Interpolation in OFDM Systems

Channel estimation and tracking methods are very critical parts of wireless Orthogonal Frequency Division Multiplexing (OFDM) systems in time and frequency selective communication channels. Interpolation has been popularly used in both domains when the channel is sampled with pilot subcarriers. The classical approach is to use the Least Square (LS) estimations to predict the channel for the pilot locations and then use Maximum Likelihood Estimation (MLE) and Minimum Mean Square Error Estimation (MMSEE) schemes to improve these initial estimations and interpolate for deriving a complete characterization of the channel. In this paper, in comb-type pilot arrangement, we propose to use the Expectation-Maximization (EM) algorithm to complement the LS scheme and propose two different approaches: (i) Using a sliding window approach based on EM estimators to interpolate, (ii) Using EM estimations on pilots instead of LS to enhance the MLE and MMSEE performance. Additionally, the necessary condition for EM to work properly is shown in the paper.