Sparsity-Aware Intelligent Massive Random Access Control for Massive MIMO Networks: A Reinforcement Learning Based Approach-Reference-Cited by-同舟云学术

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Sparsity-Aware Intelligent Massive Random Access Control for Massive MIMO Networks: A Reinforcement Learning Based Approach

Published:2024-08 Issue:8 Volume:23 Page:9730-9744
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Tang Xiao¹^ORCID,Liu Sicong¹^ORCID,Du Xiaojiang²^ORCID,Guizani Mohsen³^ORCID

Affiliation:

1. Department of Information and Communication Engineering, School of Informatics, Xiamen University, Xiamen, China

2. Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA

3. Machine Learning Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates

Funder

Natural Science Foundation of Fujian Province of China

Open Research Fund of the National Mobile Communications Research Laboratory, Southeast University

Science and Technology Key Project of Fujian Province, China

Science and Technology Key Project of Xiamen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7693/10634844/10443316.pdf?arnumber=10443316

Reference46 articles.

1. Energy-Efficient Group Paging Mechanism for QoS Constrained Mobile IoT Devices Over LTE-A Pro Networks Under 5G

2. ColO-RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms

3. Massive Random Access With Sporadic Short Packets: Joint Active User Detection and Channel Estimation via Sequential Message Passing

4. Compressive Sensing Techniques for Next-Generation Wireless Communications

5. Massive Connectivity With Massive MIMO—Part I: Device Activity Detection and Channel Estimation

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