Artificial Intelligence Aided Next-Generation Networks Relying on UAVs

被引:36
|
作者
Liu, Xiao [1 ]
Chen, Mingzhe [4 ]
Liu, Yuanwei [2 ]
Chen, Yue [3 ]
Cui, Shuguang [5 ]
Hanzo, Lajos [6 ]
机构
[1] Queen Mary Univ London, Sch Elect Engn & Comp Sci, Commun Syst Res Grp, London, England
[2] Queen Mary Univ London, London, England
[3] Queen Mary Univ London, Sch Elect Engn & Comp Sci, Telecommun Engn, London, England
[4] Princeton Univ, Elect Engn Dept, Princeton, NJ 08544 USA
[5] Chinese Univ Hong Kong, Shenzhen, Peoples R China
[6] Univ Southampton, Southampton, Hants, England
基金
英国工程与自然科学研究理事会; 欧洲研究理事会;
关键词
Resource management; Artificial intelligence; Wireless communication; Three-dimensional displays; Social networking (online); Optimization; Big Data;
D O I
10.1109/MWC.001.2000174
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we propose artificial intelligence (AI) enabled unmanned aerial vehicle (UAV) aided wireless networks (UAWN) for overcoming the challenges imposed by the random fluctuation of wireless channels, blocking and user mobility effects. In UAWN, multiple UAVs are employed as aerial base stations, which are capable of promptly adapting to the randomly fluctuating environment by collecting information about the users' position and tele-traffic demands, learning from the environment and acting upon the satisfaction level feedback received from the users. Moreover, AI enables the interaction among a swarm of UAVs for cooperative optimization of the system. As a benefit of the AI framework, several challenges of conventional UAWN may be circumvented, leading to enhanced network performance, improved reliability and agile adaptivity. As a further benefit, dynamic trajectory design and resource allocation are demonstrated. Finally, potential research challenges and opportunities are discussed.
引用
收藏
页码:120 / 127
页数:8
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