Channel Estimation Algorithms for Broadband MIMO-OFDM Systems

This paper makes a research on training sequence-based MIMO-OFDM channel estimation. In order to improve the performance of wireless MIMO-OFDM systems, a novel training sequence which is called combining cyclic comb type training symbol sequence is proposed. In this algorithm, we use the combining weighted averaging method and transmit all the training symbols cyclically at each antenna. Through simulations, it is shown that the proposed combining cyclic comb type training symbol sequence can obtain less MSE and BER, and gives higher SNR gain. So it can enhance the channel estimation performance.