Soft-output MMSE MIMO detector under MMSE channel estimation

Abstract

In reality, this is no such thing as perfect channel estimation. To improve the performance of multiple-input multiple-output (MIMO) detector under imperfect channel estimation, some novel detectors recently have been proposed by taking the channel estimation errors into account. However, all these existing detectors are with respect to maximal likelihood (ML) MIMO channel estimation. In this paper, a novel soft-output minimum mean square error (MMSE) MIMO detector is proposed with respect to MMSE MIMO channel estimation. This proposed detector takes channel estimation errors into account in the computation of the MMSE filter and LLR of each coded bit, i.e. the soft information. When compared with conventional soft-output MMSE MIMO detector, our simulation results show that the proposed novel detector can remarkably reduce the residual error floor due to the channel estimation errors, while achieving significant performance gain at the cost of negligible increase of complexity. Furthermore, it is observed from our simulation results that the proposed detector is not sensitive to the inaccuracy of channel estimation error statistics. Therefore, it can be a promising candidate to be applied in practical systems.