The lack of accurate and efficient channel estimation (CE) for multiple-input-multiple-output (MIMO) channel state information (CSI) has long been the stumbling block of near-MIMO-capacity operation. We propose a semi-blind joint CE and three-stage iterative detection/decoding scheme for near-capacity MIMO systems. The main novelty is that our decision-directed (DD) CE exploits the a posteriori information produced by the MIMO soft demapper within the inner turbo loop to select a “just sufficient number” of high-quality detected soft bit blocks or symbols for DDCE, which significantly improves the accuracy and efficiency of DDCE. Moreover, our DDCE is naturally embedded into the iterative three-stage detection/decoding process, without imposing an additional external iterative loop between the DDCE and the three-stage turbo detector/decoder. Hence, the computational complexity of our joint CE and three-stage turbo detector/decoder remains similar to that of the three-stage turbo detection/decoding scheme associated with the perfect CSI. Most significantly, the mean square error (MSE) of our DD channel estimator approaches the Cramér-Rao lower bound (CRLB) associated with the optimal-training-based CE, whereas the bit error rate (BER) of our semi-blind scheme is capable of achieving the optimal maximum-likelihood (ML) performance bound associated with the perfect CSI.
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Zhang et al. (2013) studied this question.
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