UAV Communications for Sustainable Federated Learning

被引:78
作者
Pham, Quoc-Viet [1 ]
Zeng, Ming [2 ,3 ]
Ruby, Rukhsana [3 ]
Huynh-The, Thien [4 ]
Hwang, Won-Joo [5 ]
机构
[1] Natl Univ, Korean Southeast Ctr Ind Revolut Leader Educ 4, Busan 46241, South Korea
[2] Laval Univ, Dept Elect & Comp Engn, Quebec City, PQ G1V 0A6, Canada
[3] Shenzhen Univ, Coll Comp Sci & Software Engn, Shenzhen 518060, Guangdong, Peoples R China
[4] Kumoh Natl Inst Technol, ICT Convergence Res Ctr, Gumi Si 39177, Gyeongsangbuk D, South Korea
[5] Pusan Natl Univ, Dept Biomed Convergence Engn, Yangsan 50612, South Korea
基金
新加坡国家研究基金会;
关键词
Computational modeling; Unmanned aerial vehicles; Servers; Resource management; Bandwidth; 1; f noise; Optimization; Edge computing; energy harvesting; federated learning; sustainability; UAV communications; WIRELESS; MAXIMIZATION;
D O I
10.1109/TVT.2021.3065084
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Federated learning (FL), invented by Google in 2016, has become a hot research trend. However, enabling FL in wireless networks has to overcome the limited battery challenge of mobile users. In this regard, we propose to apply unmanned aerial vehicle (UAV)-empowered wireless power transfer to enable sustainable FL-based wireless networks. The objective is to maximize the UAV transmit power efficiency, via a joint optimization of transmission time and bandwidth allocation, power control, and the UAV placement. Directly solving the formulated problem is challenging, due to the coupling of variables. Hence, we leverage the decomposition technique and a successive convex approximation approach to develop an efficient algorithm, namely UAV for sustainable FL (UAV-SFL). Finally, simulations illustrate the potential of our proposed UAV-SFL approach in providing a sustainable solution for FL-based wireless networks, and in reducing the UAV transmit power by 32.95%, 63.18%, and 78.81% compared with the benchmarks.
引用
收藏
页码:3944 / 3948
页数:5
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