Graph Neural Network for Distributed Beamforming and Power Control in Massive URLLC Networks-Reference-Cited by-同舟云学术

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Graph Neural Network for Distributed Beamforming and Power Control in Massive URLLC Networks

Published:2024-08 Issue:8 Volume:23 Page:9099-9112
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Gu Yifan¹^ORCID,She Changyang²^ORCID,Bi Suzhi¹^ORCID,Quan Zhi¹^ORCID,Vucetic Branka²^ORCID

Affiliation:

1. State Key Laboratory of Radio Frequency Heterogeneous Integration and the College of Electronics and Information Engineering, Shenzhen University, Shenzhen, Guangdong, China

2. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia

Funder

National Natural Science Foundation of China

Shenzhen Science and Technology Program

Basic and Applied Basic Research Foundation of Guangdong Province

Shenzhen Natural Science Foundation

Australian Research Council Laureate Fellowship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7693/10634832/10419173.pdf?arnumber=10419173

Reference40 articles.

1. Toward Massive, Ultrareliable, and Low-Latency Wireless Communication With Short Packets

2. Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale

3. A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems

4. Resource Allocation for Energy-Efficient MEC in NOMA-Enabled Massive IoT Networks

5. Distributed Resource Allocation for Energy Efficiency in OFDMA Multicell Networks With Wireless Power Transfer

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