Block Iterative Support Detection for Uplink Grant-Free MIMO-NOMA

Abstract

Grant-Free-Non-orthogonal multiple access (GF-NOMA) is a powerful means to reduce signaling overhead, provide a large number of connections, and support low latency requirements in 6G Internet of Things applications. However, the accuracy of multi-user detection (MUD) remains a challenge. In this letter, we propose a Block Iterative Support Detection (BISD) MUD algorithm for GF-NOMA, which exploits the spatial diversity gain and block sparsity provided by multiple-input multiple-output (MIMO) to improve the MUD accuracy of the traditional Iterative Support Detection (ISD) algorithm. The proposed BISD algorithm efficiently updates the active support set by block-wise non-zero judgment in each iteration to improve detection accuracy. Simulation results show that BISD improves the detection performance with faster convergence speed, compared with ISD and other traditional MUD algorithms for GF-NOMA.