Online Bipartite Matching for HAP Access in Space-Air-Ground Integrated Networks using Graph Neural Network-Enhanced Reinforcement Learning-Reference-Cited by-同舟云学术

Online Bipartite Matching for HAP Access in Space-Air-Ground Integrated Networks using Graph Neural Network-Enhanced Reinforcement Learning

Published:2023-05-28 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Communications Workshops (ICC Workshops)
language:
Short-container-title:

Author:

Xie Yuejiao¹,Niu Guanchong²,Pun Man-On¹,Han Zhu³

Affiliation:

1. School of Science and Engineering, the Future Network of Intelligence Institute (FNii), the Chinese University of Hong Kong,Shenzhen,China,518172

2. Guangzhou Institute of Technology, Xidian University,Guangzhou,China,510555

3. University of Houston,Department of Electrical and Computer Engineering,Houston,TX,USA,77004

Funder

National Key Research and Development Program of China

Publisher

IEEE

Link

Reference10 articles.

1. Deep policies for online bipartite matching: A reinforcement learning approach;alomrani;CoRR,2021

2. Optimal energy allocation pol-icy for wireless networks in the sky;dinh;IEEE International Conference on Communications,0

3. Neural message passing for quantum chemistry;gilmer;International Conference on Machine Learning,0

4. Learning to perform local rewriting for com-binatorial optimization;chen;Proceedings of the Advances in Neural Information Processing Systems,0

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献