AI for 5G: research directions and paradigms

被引:0
|
作者
Xiaohu You
Chuan Zhang
Xiaosi Tan
Shi Jin
Hequan Wu
机构
[1] Southeast University,National Mobile Communications Research Laboratory
[2] Chinese Academy of Engineering,undefined
来源
关键词
5G mobile communication; AI techniques; network optimization; resource allocation; unified acceleration; end-to-end joint optimization;
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摘要
Wireless communication technologies such as fifth generation mobile networks (5G) will not only provide an increase of 1000 times in Internet traffic in the next decade but will also offer the underlying technologies to entire industries to support Internet of things (IOT) technologies. Compared to existing mobile communication techniques, 5G has more varied applications and its corresponding system design is more complicated. The resurgence of artificial intelligence (AI) techniques offers an alternative option that is possibly superior to traditional ideas and performance. Typical and potential research directions related to the promising contributions that can be achieved through AI must be identified, evaluated, and investigated. To this end, this study provides an overview that first combs through several promising research directions in AI for 5G technologies based on an understanding of the key technologies in 5G. In addition, the study focuses on providing design paradigms including 5G network optimization, optimal resource allocation, 5G physical layer unified acceleration, end-to-end physical layer joint optimization, and so on.
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