A Survey on Federated Learning for Reconfigurable Intelligent Metasurfaces-Aided Wireless Networks

A Survey on Federated Learning for Reconfigurable Intelligent Metasurfaces-Aided Wireless Networks

Wireless networks are increasingly relying on machine learning (ML) paradigms to provide various services at the user level. Yet, it remains impractical for users to offload their collected data set to a cloud server for centrally training their local ML model. Federated learning (FL), which aims to...

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Bibliographic Details
Main Authors: Sree Krishna Das, Benoit Champagne, Ioannis Psaromiligkos, Yunlong Cai
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
6G
federated learning
reconfigurable intelligent metasurfaces
channel estimation
passive beamforming
resource allocation
Online Access:https://ieeexplore.ieee.org/document/10474098/

Internet

https://ieeexplore.ieee.org/document/10474098/

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