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Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey 被引量:15

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey
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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. How to explore and exploit the full potential of artificial intelligence(AI) technologies in future wireless communications such as beyond 5 G(B5 G) and 6 G 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 B5 G/6 G 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.
出处 《China Communications》 SCIE CSCD 2020年第3期58-77,共20页 中国通信(英文版)
基金 the Beijing Natural Science Foundation(4172046).
关键词 5G BEYOND 5G(B5G) 6G artificial intelligence(AI) machine learning(ML) network SLICING RESOURCE management 5G beyond 5G(B5G) 6G artificial intelligence(AI) machine learning(ML) network slicing resource management
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