Multi-Feedback Successive Interference Cancellation with Multi-Branch Processing for MIMO Systems

Abstract

In this paper, a new successive interference cancellation (SIC) strategy for multiple-input multiple output (MIMO) spatial multiplexing systems is developed to combat the error propagation (EP) in decision feedback systems. The proposed scheme employs a parallel multi-branch (MB) structure. Each branch employs a SIC with multi-feedback (MF) strategy to detects the signals according to their respective ordering pattern. The MF-SIC scheme considers the feedback diversity by using a number of selected constellation points as the feedback set if a previous decision is considered unreliable. The shadow area constraint (SAC) is proposed to reduce the computational complexity by avoiding redundant MF processing with reliable decisions. The MB-MF-SIC achieves a higher detection diversity by selecting the branch which yields the signal estimates with the best performance according to the maximum likelihood rule. The simulation results show that the MB-MF-SIC scheme successfully mitigates the EP and approaches the ML performance while requiring lower complexity than sphere decoders.