Variational Bayesian Inference Clustering-Based Joint User Activity and Data Detection for Grant-Free Random Access in mMTC-Reference-Cited by-同舟云学术

Variational Bayesian Inference Clustering-Based Joint User Activity and Data Detection for Grant-Free Random Access in mMTC

Published:2023-06-01 Issue:11 Volume:10 Page:9906-9916
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zhang Zhaoji¹^ORCID,Guo Qinghua²^ORCID,Li Ying¹^ORCID,Jin Ming³^ORCID,Huang Chongwen⁴^ORCID

Affiliation:

1. School of Telecommunications Engineering, Xidian University, Xi’an, China

2. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, Australia

3. Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China

4. College of Information Science and Electronic Engineering and the Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Zhejiang University, Hangzhou, China

Funder

China National Key Research and Development Program

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars

Ningbo Key Program of Natural Science Funds

Zhejiang Provincial Natural Science Foundation of China

National Natural Science Fund for Excellent Young Scientists Fund Program

Zhejiang University Education Foundation Qizhen Scholar Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10128761/10008195.pdf?arnumber=10008195

Reference28 articles.

1. DNN-Aided Block Sparse Bayesian Learning for User Activity Detection and Channel Estimation in Grant-Free Non-Orthogonal Random Access

2. Joint Activity and Channel Estimation for Extra-Large MIMO Systems

3. A GCICA Grant-Free Random Access Scheme for M2M Communications in Crowded Massive MIMO Systems

4. Jointly Sparse Signal Recovery and Support Recovery via Deep Learning With Applications in MIMO-Based Grant-Free Random Access

5. Orthogonal AMP for Massive Access in Channels With Spatial and Temporal Correlations

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3. Secrecy Rate Maximization based on User Clustering in Hybrid-NOMA Assisted HetNets for B5G/6G;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

4. Joint Blind Channel Estimation, Activity Detection, and Decoding for Coded Massive Random Access;2023 International Conference on Wireless Communications and Signal Processing (WCSP);2023-11-02

5. Asynchronous Grant-Free Random Access: Partially Uni-Directional Message Passing for Joint User Activity Detection and Channel Estimation;2023 International Conference on Wireless Communications and Signal Processing (WCSP);2023-11-02