Future Vision on Artificial Intelligence Assisted Green Energy Efficiency Network

Release Date:2023-06-25 Author:CHEN Jiajun, GAO Yin, LIU Zhuang, LI Dapeng

Abstract: To meet the key performance requirement of the 5G network and the demand of the growing number of mobile subscribers, millions of base stations are being constructed. 5G New Radio is designed to enable denser network deployments, which raises significant concerns about network energy consumption. Machine learning (ML), as a kind of artificial intelligence (AI) technologies, can enhance network optimization performance and energy efficiency. In this paper, we propose AI/ML-assisted energy-saving strategies to achieve optimal performance in terms of cell shutdown duration and energy efficiency. To realize network intelligence, we put forward the concept of intrinsic AI, which integrates AI into every aspect of wireless communication networks.

 

Keywords: machine learning; energy efficiency; traffic distribution; load prediction; intrinsic AI

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