Distributed Multi-Agent Reinforcement Learning for Heterogeneous NOMA-ALOHA Systems

Wu, Xueyu, Ko, Youngwook and Tyrrell, Andy orcid.org/0000-0002-8533-2404 (2025) Distributed Multi-Agent Reinforcement Learning for Heterogeneous NOMA-ALOHA Systems. IEEE Transactions on Cognitive Communications and Networking. pp. 1902-1912. ISSN 2332-7731

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Item Type: Article
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© 2024 IEEE. This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

Keywords: Reinforcement learning,distributed learning,NORA,Q-Learning,multiple access control
Dates:
  • Accepted: 29 September 2024
  • Published: 12 June 2025
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Electronic Engineering (York)
Depositing User: Pure (York)
Date Deposited: 07 Oct 2024 13:00
Last Modified: 26 Jun 2025 23:18
Published Version: https://doi.org/10.1109/TCCN.2024.3474709
Status: Published
Refereed: Yes
Identification Number: 10.1109/TCCN.2024.3474709
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Filename: Distributed_RL_for_Heterogeneous_NORA_V1.pdf

Description: Distributed_RL_for_Heterogeneous_NORA V1

Licence: CC-BY 2.5

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