MIMO channel estimation: optimal training and tradeoffs between estimation techniques

Channel estimation in multiple-input multiple-output (MIMO) wireless communication systems plays a key role in the performance of space-time decoders that depends on the accuracy of the channel knowledge. In this paper, we study the performance of MIMO channel estimation using training sequences. The least squares (LS), minimum-mean-square error (MMSE), and a new scaled LS (SLS) approaches to the channel estimation are studied and the optimal choice of training signals is investigated for each of these techniques.