RLS Channel Estimation and Data Detection in Space-Time Coded MIMO-OFDM Systems

Multiple-input and multiple-out (MIMO) can increase the channel capacity. Orthogonal frequency division multiplexing (OFDM) can mitigate the effects of delay spread in the frequency selective-fading channels. And space-time coding techniques can improve the system performance. So the combination of MIMO, OFDM and space-time coding techniques (space-time coded MIMO-OFDM) is an attractive method for high-data-rate wireless applications. Moreover, accurate channel state information is essential to diversity combination, coherent detection and decoding in a space-time coded MIMO-OFDM system. Therefore, a method of RLS (recursive least squares) channel estimation and maximum likelihood (ML) data detection is proposed in this paper. The RLS filter is employed in proposed channel estimation method. Simulation results confirm that this proposed RLS channel estimation method has better performances than the LMS (least mean square) or LS (least square) channel estimation method at the cost of moderate computational complexity.