Markov Chain Monte Carlo MIMO Detection for Systems with Imperfect Channel State Information

The problem of data detection in MIMO systems is usually studied under the assumption of perfect channel knowledge at the receiver. In practice, however, only a (potentially very poor) estimate of the channel is available. It has been shown that detection algorithms which take the unreliability of the channel estimate into account can significantly outperform their mismatched counterparts (i.e., detectors which use the estimate in lieu of the true channel matrix). In this paper, we extend the Markov Chain Monte Carlo (MCMC) MIMO detector to the case of imperfect channel knowledge. Due to the low complexity of the MCMC algorithm, this technique is also applicable in systems where brute force approaches are computationally infeasible.