Explainable Decentralized Federated Learning for Energy-Efficient Base Station Sleep Control
Conference paper
Movahedkor, N., Shahbazian, R. and Ghorashi, S. 2025. Explainable Decentralized Federated Learning for Energy-Efficient Base Station Sleep Control. 2025 IEEE 31st International Conference on Telecommunications (ICT). IEEE. https://doi.org/10.1109/ICT65093.2025.11046230
Authors | Movahedkor, N., Shahbazian, R. and Ghorashi, S. |
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Type | Conference paper |
Abstract | Given the capacity and performance boosts offered by the 5G cellular networks, energy consumption at the base stations (BSs) has increased tremendously. This paper proposes a decentralized federated learning (DFL)-based intelligent BS switching, integrated with explainable artificial intelligence (XAI) methods, to mitigate the concerns for energy consumption in dense 5G networks. This entails collaboration among distributed but interconnected networks to learn the best policies for BS switching without any central controller, so that knowledge sharing can be ensured while privacy and communication efficiency are maintained. Very importantly, we further researched the XAI techniques to provide better transparency on the decision-making of the switching control agent and create some trust in the learned policies. Such explainability allows us to derive the most important factors affecting BS switching decisions and how these contribute in enabling energy savings while maintaining quality of service (QoS). Extensive simulations conducted to validate our proposed framework in presenting valuable XAI analysis have elaborately provided the basis for understanding the learned strategies and key factors driving energy-efficient BS management. |
Year | 2025 |
Conference | 2025 IEEE 31st International Conference on Telecommunications (ICT) |
Publisher | IEEE |
Accepted author manuscript | License File Access Level Anyone |
Publication dates | |
Online | 26 Jun 2025 |
Publication process dates | |
Accepted | 15 Mar 2025 |
Completed | 29 Apr 2025 |
Deposited | 18 Jun 2025 |
Journal citation | pp. 1-5 |
ISSN | 2993-1916 |
2771-4233 | |
Book title | 2025 31st International Conference on Telecommunications (ICT) |
ISBN | 979-8-3315-1447-1 |
979-8-3315-1448-8 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ICT65093.2025.11046230 |
Web address (URL) of conference proceedings | https://ieeexplore.ieee.org/xpl/conhome/1002158/all-proceedings |
Copyright holder | © 2025 IEEE |
Additional information | Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
https://repository.uel.ac.uk/item/8zvqx
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Accepted author manuscript
Ghorashi-ICT-2025.pdf | ||
License: All rights reserved | ||
File access level: Anyone |
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