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Complexity Reduction of MMSE Method for Iterative MIMO Systems

The multiple-input multiple-output (MIMO) wireless technology combined with iterative decoding can meet the demands of future needs. The major issue of utilizing the potential of iterative detection and decoding method is its computational complexity due to complex signal detection methods. Another issue is nearly all detection steps are repeated in each iteration. One of the promising detection techniques for multiple-input multiple-output (MIMO) system is linear detector known as minimum mean squared error (MMSE) which utilizes soft information feedback from turbo decoder for cancellation steps can be employed due to lower complexity compared to several existing methods. In this paper, we apply an approach which can reduce the complexity of soft interference cancellation-minimum mean squared error (SIC-MMSE) signal detection method without error rate performance degradation. We observe that soft information of few transmitted symbol reach at very high reliability, and thus an approximation approach can be used to perform interference cancellation step for these symbols. Simulation results are presented to demonstrate the bit error rate performance of the proposed signal detection method.