We present a low complexity soft detector for multiple-input multiple-output (MIMO) channels. Our proposed minimum mean square error successive interference cancellation (MMSE-SIC) detector is based on a regularization mechanism which reduces error propagation in the channel iterative decoder. Although our proposed detector is easy to implement and has a complexity order that is cubic in the number of transmit antennas, it can reach the performance of the soft max-log maximum-likelihood detector (MLD) under realistic system assumptions, as demonstrated in our simulations.
We evaluate the capacity bounds and the system performance of a set of detection algorithms for multiple-input multiple-output (MIMO) systems focusing on low complexity interference cancellation methods. Since detection and decoding in a bit-interleaved coded modulation system (BICM) is performed separately, the performance in terms of bit error rate depends on both, the signal constellation and the channel encoder design. In order to find a universal measure for the performance of the detection stage, we evaluate the mutual information of the transmit signal and the a-posteriori bit hypotheses probabilities of the respective decoder. The outcome of our analysis provides bounds for the achievable rates using optimal and suboptimal detection algorithms.
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