Low-Complexity MIMO Detection: A Mixture of Basic Techniques for Near-Optimal Error Rate

Abstract

The research of finding better ways for multiple-input multiple-output signal detection is important and still goes on. In this brief, a low-complexity detection method mainly with basic and hardware-friendly operations, i.e., reduced-complexity zero forcing, successive interference cancelation, and single-symbol maximum likelihood detection with $M$ - algorithm, is proposed. Essentially, this detection method has fixed complexity and can achieve near-optimal error-rate performance with affordable complexity in many cases. Results show that, in terms of giving a good tradeoff between the implementation complexity and error rate, the proposed low-complexity detection scheme can remarkably outperform some state-of-the-art counterparts, including the conventional ML detector employing QR-decomposition and $M$ - algorithm and fixed-complexity sphere decoder, and owns an error rate very close to that of the optimal one.