Multi-branch successive interference cancellation for MIMO spatial multiplexing systems

In this paper we propose a novel successive interference cancellation (SIC) strategy for multiple-input multiple-output (MIMO) spatial multiplexing systems based on multiple interference cancellation branches. The proposed detection structure employs SICs on several parallel branches which are equipped with different ordering patterns so that each branch produces a symbol estimate vector by exploiting a certain ordering pattern. The novel detector, therefore, achieves higher detection diversity by selecting the branch which yields the estimates with the best performance according to the selection rule. We consider three selection rules for the proposed detector, namely, maximum likelihood (ML), minimum mean square error (MMSE), constant modulus (CM) criteria. The simulation results reveal that our scheme successfully mitigates the error propagation and approaches the performance of the optimal ML detector, while requiring a significantly lower complexity than the ML detector.