Iterative Joint Detection and ORBGRAND for Massive Multi-User MIMO

Abstract

Multi-user multi-input multi-output (MU-MIMO) is a key enabler for next-generation wireless systems, but its performance is often limited by strong interference from inter-user channel correlations and the lack of decoding-aware detection strategies. To address this challenge, we propose a joint iterative detection and decoding algorithm that consists of detection, ordered reliability bits guessing random additive noise decoding (ORBGRAND), and hard/soft parallel interference cancellation (PIC) switching, in consideration of inter-user channel correlation and decoding failure. Simulation results demonstrate that the proposed scheme outperforms state-of-the-art baselines, providing a significantly improved block error rate (BLER). These results highlight the potential of the proposed method as an efficient and robust solution for coded MU-MIMO systems.