Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

被引:0
|
作者
Lin, Mengting [1 ]
Zhao, Youping [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
基金
北京市自然科学基金;
关键词
5G; beyond 5G (B5G); 6G; artificial intelligence (AI); machine learning (ML); network slicing; resource management; COGNITIVE RADIO; MICRO OPERATORS; 5G; NETWORKS;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
How to explore and exploit the full potential of artificial intelligence (AI) technologies in future wireless communications such as beyond 5G (B5G) and 6G is an extremely hot inter-disciplinary research topic around the world. On the one hand, AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities. On the other hand, embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks. This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective, not only considering the radio resource (e.g.. spectrum) management but also other types of resources such as computing and caching. We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.
引用
收藏
页码:58 / 77
页数:20
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