Version 1
: Received: 5 April 2024 / Approved: 7 April 2024 / Online: 7 April 2024 (10:50:09 CEST)
How to cite:
Ezzedine, Z.; Khalil, A.; Zeddini, B.; Ouslimani, H. A Survey on Green Enablers: Challenging Study for AI-based 5G Energy Efficiency Network. Preprints2024, 2024040474. https://doi.org/10.20944/preprints202404.0474.v1
Ezzedine, Z.; Khalil, A.; Zeddini, B.; Ouslimani, H. A Survey on Green Enablers: Challenging Study for AI-based 5G Energy Efficiency Network. Preprints 2024, 2024040474. https://doi.org/10.20944/preprints202404.0474.v1
Ezzedine, Z.; Khalil, A.; Zeddini, B.; Ouslimani, H. A Survey on Green Enablers: Challenging Study for AI-based 5G Energy Efficiency Network. Preprints2024, 2024040474. https://doi.org/10.20944/preprints202404.0474.v1
APA Style
Ezzedine, Z., Khalil, A., Zeddini, B., & Ouslimani, H. (2024). A Survey on Green Enablers: Challenging Study for AI-based 5G Energy Efficiency Network. Preprints. https://doi.org/10.20944/preprints202404.0474.v1
Chicago/Turabian Style
Ezzedine, Z., Besma Zeddini and Habiba Ouslimani. 2024 "A Survey on Green Enablers: Challenging Study for AI-based 5G Energy Efficiency Network" Preprints. https://doi.org/10.20944/preprints202404.0474.v1
Abstract
In today's world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in the 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. To address this challenge, advanced wireless technologies have been incorporated into the design of 5G networks across various network layers. Given the rapid advancements in Artificial Intelligence (AI) and emerging technology trends such as Machine Learning (ML), which is considered a subset of AI, the integration of such trends into 5G networks has become a significant area of research. The primary objective of this survey is to analyze AI 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.
Keywords
artificial intelligence (AI); internet of things (IoT); key performance indicators (KPIs); machine learning (ML); quality of service (QoS); energy efficiency
Subject
Engineering, Telecommunications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
