Resource allocation in wireless networks with federated learning: Network adaptability and learning acceleration

Resource allocation in wireless networks with federated learning: Network adaptability and learning acceleration

Deep reinforcement learning can effectively address resource allocation in wireless networks. However, its learning speed may be slower in more complex networks and a new policy should be learned for a newly-arrived system due to a lack of network adaptability. To address these issues, we propose a...

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Bibliographic Details
Main Authors: Hyun-Suk Lee, Da-Eun Lee
Format: Article
Language:English
Published: Elsevier 2022-03-01
Series:ICT Express
Subjects:
Deep learning
Federated learning
Reinforcement learning
Resource allocation
Wireless networks
Online Access:http://www.sciencedirect.com/science/article/pii/S2405959522000194

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http://www.sciencedirect.com/science/article/pii/S2405959522000194

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