Dynamic Multichannel Access via Multi-agent Reinforcement Learning: Throughput and Fairness Guarantees-Reference-Cited by-同舟云学术

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Dynamic Multichannel Access via Multi-agent Reinforcement Learning: Throughput and Fairness Guarantees

Published:2021 Issue: Volume: Page:1-1
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Sohaib Muhammad,Jeong Jongjin,Jeon Sang-Woon

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7693/4656680/09619960.pdf?arnumber=9619960

Cited by 4 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

1. Energy Conservation in Wireless Body Area Network Using Optimal Route Selection and Node Configuration;2023 International Conference on Data Science and Network Security (ICDSNS);2023-07-28

2. THz Communications: A Key Enabler for Future Cellular Networks;IEEE Access;2023

3. Load-Aware Distributed Resource Allocation for MF-TDMA Ad Hoc Networks: A Multi-Agent DRL Approach;IEEE Transactions on Network Science and Engineering;2022-11-01

4. Reinforcement Learning for NOMA-ALOHA Under Fading;IEEE Transactions on Communications;2022-10

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