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A Survey on Green Enablers: A Study on the Energy Efficiency of AI-Based 5G Networks
Zeinab Ezzeddine1,2, Ayman Khalil3, Besma Zeddini2
1Laboratory of Electrochemistry of Materials for Energetics (LEME) EA 4416, University Paris, 92410 Nanterre, France.
Abstract:
In today's world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in 5th-generation (5G) networks. However, it is crucial to ensure that these energy-saving measures do not compromise the Key Performance Indicators (KPIs), such as user experience, quality of service (QoS), or other important aspects of the network. Advanced wireless technologies have been integrated into 5G network designs at multiple network layers to address this difficulty. The integration of emerging technology trends, such as machine learning (ML), which is a subset of artificial intelligence (AI), and AI's rapid improvements have made the integration of these trends into 5G networks a significant topic of research. The primary objective of this survey is to analyze AI's integration into 5G networks for enhanced energy efficiency. By exploring this intersection between AI and 5G, we aim to identify potential strategies and techniques for optimizing energy consumption while maintaining the desired network performance and user experience.
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