JOURNAL ARTICLE

Bidirectional Side Information Aided Compressed Sensing Multiuser Detection for Uplink GF-NOMA

Yaoxin GaoJianping ZhengBo Li

Year: 2022 Journal:   2022 IEEE Wireless Communications and Networking Conference (WCNC) Pages: 2148-2153

Abstract

Grant-free non-orthogonal multiple access (GF-NOMA) is considered as an important technology in massive machine-type communications. In this paper, we study the multiuser detection (MUD) of uplink GF-NOMA with temporal-correlated active users. To utilize the temporal correlation in both directions, the bidirectional (BD) side information aided (SIA) compressed sensing (CS) MUD is proposed here for both the cases with known and unknown user sparsity level. Concretely, the bidirectional dynamic CS MUD (BD-DCS-MUD) is first proposed in the case with known user sparsity level. In BD-DCS-MUD, the temporal correlation information between adjacent time slots in both directions is utilized by performing forward DCS-MUD followed by backward DCS-MUD. For the case with unknown user sparsity level, the SIA sliding-window block orthogonal matching pursuit (SIA-SW-BOMP) is proposed. In SIA-SW-BOMP, the backward temporal correlation information is also utilized by SW decoding strategy, besides the forward information utilization through BOMP. Simulation results show that the proposed BD SIA CS MUDs can achieve better performance than their forward counterparts especially for the scenario of large user sparsity level, with some increased complexity.

Keywords:
Telecommunications link Noma Computer science Compressed sensing Decoding methods Matching pursuit Multiuser detection Block (permutation group theory) Real-time computing Electronic engineering Algorithm Telecommunications Engineering Mathematics Code division multiple access

Metrics

2
Cited By
0.74
FWCI (Field Weighted Citation Impact)
18
Refs
0.54
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Wireless Communication Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Sparse and Compressive Sensing Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
© 2026 ScienceGate Book Chapters — All rights reserved.