Multi-Feedback Successive Interference Cancellation for Multiuser MIMO Systems

TL;DR

This paper introduces a low-complexity MF-SIC algorithm with shadow area constraints for uplink MU-MIMO systems, enhancing interference cancellation and detection diversity, and demonstrating significant performance improvements over conventional methods.

Contribution

It proposes a novel MF-SIC algorithm with shadow area constraints and multi-branch processing, improving interference cancellation and detection diversity in MU-MIMO systems.

Findings

Significant performance gains over conventional SIC.

Approaches the optimal detector in simulations.

Low computational complexity comparable to traditional SIC.

Abstract

In this paper, a low-complexity multiple feedback successive interference cancellation (MF-SIC) strategy is proposed for the uplink of multiuser multiple-input multiple-output (MU-MIMO) systems. In the proposed MF-SIC {algorithm with shadow area constraints (SAC)}, an enhanced interference cancellation is achieved by introducing {constellation points as the candidates} to combat the error propagation in decision feedback loops. We also combine the MF-SIC with multi-branch (MB) processing, which achieves a higher detection diversity order. For coded systems, a low-complexity soft-input soft-output (SISO) iterative (turbo) detector is proposed based on the MF and the MB-MF interference suppression techniques. The computational complexity of the MF-SIC is {comparable to} the conventional SIC algorithm {since very little additional complexity is required}. {Simulation} results show that the algorithms significantly outperform the conventional SIC scheme and {approach} the optimal detector.