Extended Kalman filtering-based channel estimation for space-time coded MIMO-OFDM systems

Abstract

A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system is considered as a solution to the future wideband wireless communication system. This paper proposes an extended Kalman filtering-based (EKF-based) channel estimation method for space-time coded MIMO-OFDM systems. The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics. In comparison with the least square (LS) and the least mean square (LMS) methods, the EKF-based approach has a better performance in theory. Computer simulations demonstrate the proposed method outperforms the LS and LMS methods. Therefore it can offer dramatic system performance improvement at a modest cost of computational complexity.