中文版 | English
Title

Distributed Over-the-Air Computing for Fast Distributed Optimization: Beamforming Design and Convergence Analysis

Author
Publication Years
2022
DOI
Source Title
ISSN
1558-0008
EISSN
1558-0008
VolumePPIssue:99Pages:1-1
Abstract
Distributed optimization finds a wide range of applications ranging from machine learning to vehicle platooning. To overcome the bottleneck caused by the required extensive message exchange, we propose in this work the framework of distributed over-the-air computing (AirComp) to realize a one-step aggregation for distributed optimization. Equivalently, the technique superimposes multiple instances of conventional AirComp processes, giving rise to the challenge of jointly designing multicast beamforming at devices to rein in errors due to interference and channel distortion. We consider two design criteria. One is to minimize the sum AirComp error (i.e., sum mean-squared error (MSE)) with respect to the desired average-functional values. An efficient solution approach is proposed by transforming the non-convex beamforming problem into an equivalent concave-convex fractional program and solving it by nesting convex programming into a bisection search. The other one, called zero-forcing (ZF) multicast beamforming, is to force the received over-the-air aggregated signals at devices to be equal to the desired functional values, where the optimal beamforming admits closed form. Last, the convergence of a classic distributed optimization algorithm is analyzed. The distributed AirComp is found experimentally to accelerate convergence by dramatically reducing communication latency.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
First
Funding Project
National Key Research and Development Program of China[2019YFB1802800] ; National Natural Science Foundation of China[62071212] ; Guangdong Basic and Applied Basic Research Foundation[2019B1515130003] ; Research Grants Council of the Hong Kong Special Administrative Region[HKU RFS2122-7S04] ; Hong Kong Research Grants Council[17208319] ; Shenzhen Science and Technology Program[JCYJ20200109141414409]
WOS Research Area
Engineering ; Telecommunications
WOS Subject
Engineering, Electrical & Electronic ; Telecommunications
WOS Accession No
WOS:000927934500018
Publisher
ESI Research Field
COMPUTER SCIENCE
Data Source
IEEE
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9958941
Citation statistics
Cited Times [WOS]:2
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/414590
DepartmentDepartment of Electrical and Electronic Engineering
Affiliation
1.Department of Electrical and Electronics Engineering, Southern University of Science and Technology, Shenzhen, China
2.Department of Electrical and Electronics Engineering, The University of Hong Kong, Hong Kong, China
First Author AffilicationDepartment of Electrical and Electronic Engineering
First Author's First AffilicationDepartment of Electrical and Electronic Engineering
Recommended Citation
GB/T 7714
Zhenyi Lin,Yi Gong,Kaibin Huang. Distributed Over-the-Air Computing for Fast Distributed Optimization: Beamforming Design and Convergence Analysis[J]. IEEE Journal on Selected Areas in Communications,2022,PP(99):1-1.
APA
Zhenyi Lin,Yi Gong,&Kaibin Huang.(2022).Distributed Over-the-Air Computing for Fast Distributed Optimization: Beamforming Design and Convergence Analysis.IEEE Journal on Selected Areas in Communications,PP(99),1-1.
MLA
Zhenyi Lin,et al."Distributed Over-the-Air Computing for Fast Distributed Optimization: Beamforming Design and Convergence Analysis".IEEE Journal on Selected Areas in Communications PP.99(2022):1-1.
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