Mixed Gibbs Sampling Detector in High-Order Modulation Large-Scale MIMO Systems

TL;DR

This paper introduces a neighborhood-restricted Mixed Gibbs Sampling detector for large-scale MIMO systems with high-order modulation, significantly improving convergence and performance without extra complexity.

Contribution

It proposes a novel neighborhood limitation (d-sMGS) approach that enhances MGS detection in high-order modulation LS-MIMO systems, especially under high system loading.

Findings

Substantially improved MGS convergence with 64-QAM.

No additional computational complexity per iteration.

Better performance vs. complexity tradeoff at high system loading.

Abstract

A neighborhood restricted Mixed Gibbs Sampling (MGS) based approach is proposed for low-complexity high-order modulation large-scale Multiple-Input Multiple-Output (LS-MIMO) detection. The proposed LS-MIMO detector applies a neighborhood limitation (NL) on the noisy solution from the MGS at a distance d - thus, named d-simplified MGS (d-sMGS) - in order to mitigate its impact, which can be harmful when a high order modulation is considered. Numerical simulation results considering 64-QAM demonstrated that the proposed detection method can substantially improve the MGS algorithm convergence, whereas no extra computational complexity per iteration is required. The proposed d-sMGS-based detector suitable for high-order modulation LS-MIMO further exhibits improved performance vs. complexity tradeoff when the system loading is high, i.e., when K >= 0.75. N. Also, with increasing the number of dimensions, i.e., increasing the number of antennas and/or modulation order, a smaller restriction of 2-sMGS was shown to be a more interesting choice than 1-sMGS.