Joint blind maximum likelihood MIMO channel tracking and detection

In this paper, different schemes of joint blind channel tracking and data detection algorithms based on maximum likelihood (ML) algorithm for time-varying flat fading multiple-input multiple-output (MIMO) channels are introduced. If the channel model is known in the receiver, ML can present the best performance. The performance and tracking behavior of the proposed algorithms is justified via various simulations for first order time-varying MIMO channels and it is shown that in all cases, the decision-directed ML (DDML) algorithm with separate ML detection and tracking has the best performance.