Future Vision on Artificial Intelligence Assisted Green Energy Efficiency Network

作     者：CHEN Jiajun GAO Yin LIU Zhuang LI Dapeng CHEN Jiajun;GAO Yin;LIU Zhuang;LI Dapeng

作者机构：State Key Laboratory of Mobile Network and Mobile Multimedia TechnologyShenzhen 518055China Wireless Product R&D InstituteZTE CorporationShanghai 201203China 

出 版 物：《ZTE Communications》 (中兴通讯技术（英文版）)

年 卷 期：2023年第21卷第2期

页      面：34-39页

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：machine learning energy efficiency traffic distribution load prediction intrinsic AI 

摘      要：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 *** learning(ML),as a kind of artificial intelligence(AI)technologies,can enhance network optimization performance and energy *** this paper,we propose AI/ML-assisted energy-saving strategies to achieve optimal performance in terms of cell shutdown duration and energy *** realize network intelligence,we put forward the concept of intrinsic AI,which integrates AI into every aspect of wireless communication networks.