Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges, and Future Directions

Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges, and Future Directions

Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart services and innovative applications. Such a context urges a heavy usage of Machine Learning (ML) techniques, particularly Deep Learning (DL), to foster innovation and ease the deployment of intelligent network...

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Bibliographic Details
Main Authors: Houda Hafi, Bouziane Brik, Pantelis A. Frangoudis, Adlen Ksentini, Miloud Bagaa
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
6G networks
wireless communication
federated deep learning
split deep learning
split federated learning
Online Access:https://ieeexplore.ieee.org/document/10385040/

Internet

https://ieeexplore.ieee.org/document/10385040/

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