中文版 | English
Title

ISAC-Accelerated Edge Intelligence: Framework, Optimization, and Analysis

Author
Publication Years
2023
DOI
Source Title
ISSN
2473-2400
EISSN
2473-2400
VolumePPIssue:99Pages:1-1
Abstract
Conventionally, the sensing and communication stages for edge intelligence systems are executed sequentially, leading to an excessive time of dataset generation and uploading. To combat the weakness, this paper proposes to accelerate edge intelligence via integrated sensing and communication (ISAC), where the sensing and communication stages are merged to make the best use of the wireless signals for the dual purpose of dataset generation and uploading. For the proposed ISAC-accelerated edge intelligence system, the resource allocation and beamforming should be jointly optimized to exploit the underlying ISAC benefits. We formulate a joint resource allocation and beamforming optimization problem. Despite the non-convexity, we obtain globally optimal solutions assuming that the constant maximal transmits power, and devise an alternating optimization algorithm for the original problem without such assumption. Furthermore, we analyze the ISAC acceleration gain of the proposed system over that of the conventional edge intelligence system. Both theoretic analysis and simulation results show that ISAC accelerates the conventional edge intelligence system when the duration of generating a sample is more than that of uploading a sample. Otherwise, the ISAC acceleration gain vanishes or even is negative. In this case, we derive a sufficient condition for positive ISAC acceleration gain.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Others
Funding Project
National Natural Science Foundation of China["62171213","62001310"] ; Open Research Fund from the Guangdong Laboratory of Artificial Intelligence and Digital Economy[GML-KF-22-17] ; Guangdong Basicand Applied Basic Research Project["2021B1515120067","2022A1515010109"]
WOS Research Area
Telecommunications
WOS Subject
Telecommunications
WOS Accession No
WOS:000944152100036
Publisher
Scopus EID
2-s2.0-85147228299
Data Source
IEEE
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10005142
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/424540
DepartmentDepartment of Electrical and Electronic Engineering
Affiliation
1.Guangdong Laboratory of Artificial Intelligence and Digital Economy, Shenzhen, China
2.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
3.Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China
4.Shenzhen Research Institute of Big Data, Shenzhen, China
5.5GIC and6GIC, Institute for Communication Systems, University of Surrey, Guildford, UK
Recommended Citation
GB/T 7714
Tong Zhang,Guoliang Li,Shuai Wang,et al. ISAC-Accelerated Edge Intelligence: Framework, Optimization, and Analysis[J]. IEEE Transactions on Green Communications and Networking,2023,PP(99):1-1.
APA
Tong Zhang,Guoliang Li,Shuai Wang,Guangxu Zhu,Gaojie Chen,&Rui Wang.(2023).ISAC-Accelerated Edge Intelligence: Framework, Optimization, and Analysis.IEEE Transactions on Green Communications and Networking,PP(99),1-1.
MLA
Tong Zhang,et al."ISAC-Accelerated Edge Intelligence: Framework, Optimization, and Analysis".IEEE Transactions on Green Communications and Networking PP.99(2023):1-1.
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