Channel Estimation With Expectation Maximization and Historical Information Based Basis Expansion Model for Wireless Communication Systems on High Speed Railways

Abstract

This paper proposes a blind channel estimator based on expectation maximization algorithm and historical information-based basis expansion model for uplink wireless communication systems on high speed railways. The information of basis matrices is obtained from the uplink data of the past trains at the base station (BS). With the known basis matrices at the BS, our suggested estimator can estimate the basis coefficients and recover the channel parameters without requiring training symbols. The modified Cramer–Rao bound is derived for the estimated basis coefficients and the computational complexity of the proposed estimator is analyzed. Numerical results are then provided to corroborate our studies. It is shown that the proposed estimator outperforms existing data-aided estimators, including least square and linear minimum mean square error.