High Order M-QAM Massive MIMO Detector with Low Computational Complexity for 5G Systems

TL;DR

This paper introduces a low-complexity detection algorithm for high-order M-QAM massive MIMO systems, significantly improving BER performance in 5G scenarios, especially at low SNRs.

Contribution

The work proposes a real-domain Schnorr Euchner enumeration with K-best algorithm that reduces computational complexity for high-order MIMO detection in 5G systems.

Findings

Outperforms existing detection algorithms in complexity and BER.

Effective in low SNR regions for massive MIMO systems.

Validated on systems up to 120 antennas with 1024-QAM.

Abstract

In this work, the behaviour of bit error rates for both conventional and massive MIMO systems with high order constellations, which are essential to achieve spectral efficiency for 5G standard communications, has been evaluated. We have used real-domain Schnorr Euchner enumeration with K-best algorithm to reduce computational complexity of detection. The results, presented in this letter, have outperformed existing detection algorithms in terms of complexity and BER, especially in low SNR regions, for both massive and conventional MIMO systems. We performed simulations for N $\times$ N MIMO system, where N = 8, 25, 40, 50, 60, 80, 100 and 120, for both 256-QAM and 1024-QAM high order transmission systems as per the latest 3GPP standards for 5G systems and beyond. All the analyses and results that are given in this letter are from our MIMO detector, prior to usage of error correction decoder.