Multiuser Detection of GF-NOMA With Dynamic-Active Users and Temporal-Correlated Channels

In this letter, an efficient multiuser detection (MUD) is proposed for the grant-free non-orthogonal multiple access in the scenario with dynamic active users and unknown temporal-correlated channels. The proposed MUD performs active user and slot detection, channel estimation, and data detection si...

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Bibliographic Details
Published in:IEEE communications letters 2022-10, Vol.26 (10), p.2380-2384
Main Authors: Gao, Yaoxin, Zheng, Jianping, Li, Bo
Format: Article
Language:English
Subjects:
Channel estimation
Channels
compressed sensing
Correlation
Fading channels
GF-NOMA
Heuristic algorithms
Iterative methods
Matching pursuit algorithms
Message passing
Mud
Multiuser detection
Nonorthogonal multiple access
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Summary:In this letter, an efficient multiuser detection (MUD) is proposed for the grant-free non-orthogonal multiple access in the scenario with dynamic active users and unknown temporal-correlated channels. The proposed MUD performs active user and slot detection, channel estimation, and data detection simultaneously by iterative generalized approximate message passing (GAMP) and message passing (MP) over the joint factor graph. Concretely, GAMP is to decouple the transmissions of different users, and MP to update channel and user activity information. Finally, computer simulations are provided to validate the performance of the proposed method.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2022.3189342