Multiple feedback successive interference cancellation with iterative decoding for point-to-point MIMO systems

We investigate successive interference cancellation (SIC) detectors that can achieve a close to optimum BER performance in spatial multiplexed multi-input multi-output (SM-MIMO) systems. We propose a low-complexity interference suppression strategy, in which an enhanced SIC is devised by introducing the feedback diversity to combat the error propagation in decision feedback loops. In order to constrain the complexity introduced by the multiple feedback (MF) processing, a strategy called shadow area constraint (SAC) is developed to save the additional complexity by avoiding redundant MF processing with reliable decisions. Based on the MF and SAC algorithms, in this paper, we derive a MF aided soft-input soft-output SIC detector for iterative (turbo) MIMO systems, the feedback diversity is introduced in the detection procedure of each spatial layer to compute the extrinsic information of the coded bits. The simulations performed on an iterative detection and decoding (IDD) scheme over frequency flat fading channels demonstrate that the proposed scheme significantly outperforms the conventional SIC schemes with low computational effort.