中文版 | English
Title

Multi-Vehicle Tracking and ID Association Based on Integrated Sensing and Communication Signaling

Author
Corresponding AuthorYuan,Weijie
Publication Years
2022-09-01
DOI
Source Title
ISSN
2162-2337
EISSN
2162-2345
Volume11Issue:9Pages:1960-1964
Abstract

The integrated sensing and communication (ISAC) technology, which performs vehicle state sensing and communications simultaneously, has been widely regarded as a key to enable future intelligent vehicular networks. However, the communications information is in general vehicle-specific, which requires the RSU to distinguish vehicle identities (IDs). Conventionally, the vehicles feed back their IDs to the RSU, since they are not contained in the sensing echoes. This letter develops a novel approach for multi-vehicle tracking and ID association using the ISAC signals. In particular, the ID association is done by comparing the similarity of the distributions of estimated and predicted locations based on the Kullback-Leibler divergence (KLD). With the aid of the proposed approach, frequent uplink ID feedback is avoided, leading to a reduced communication overhead as well as latency. We further design a high-efficiency predictive beamforming scheme, which predicts the angular parameters in the following time instant relying on the estimated states. Simulation results show that our proposed scheme can effectively associate different vehicle IDs and improve the communications performance.

Keywords
URL[Source Record]
Indexed By
SCI ; EI
Language
English
SUSTech Authorship
Corresponding
Funding Project
National Key Research and Development Program of China[2021YFB2900200] ; National Natural Science Foundation of China[62101232] ; Guangdong Provincial Natural Science Foundation[2022A1515011257]
WOS Research Area
Computer Science ; Engineering ; Telecommunications
WOS Subject
Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS Accession No
WOS:000852215400042
Publisher
EI Accession Number
20222912379271
EI Keywords
Array Processing ; Beamforming ; Signal To Noise Ratio ; Vehicle To Vehicle Communications
ESI Classification Code
Electromagnetic Waves In Relation To Various Structures:711.2 ; Information Theory And Signal Processing:716.1 ; Radio Systems And Equipment:716.3
Data Source
Web of Science
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9820762
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/356242
DepartmentDepartment of Electrical and Electronic Engineering
Affiliation
1.China Academy of Information and Communications Technology, Beijing, China
2.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
Corresponding Author AffilicationDepartment of Electrical and Electronic Engineering
Recommended Citation
GB/T 7714
Wang,Zhiqin,Han,Kaifeng,Jiang,Jiamo,et al. Multi-Vehicle Tracking and ID Association Based on Integrated Sensing and Communication Signaling[J]. IEEE Wireless Communications Letters,2022,11(9):1960-1964.
APA
Wang,Zhiqin,Han,Kaifeng,Jiang,Jiamo,Liu,Fan,&Yuan,Weijie.(2022).Multi-Vehicle Tracking and ID Association Based on Integrated Sensing and Communication Signaling.IEEE Wireless Communications Letters,11(9),1960-1964.
MLA
Wang,Zhiqin,et al."Multi-Vehicle Tracking and ID Association Based on Integrated Sensing and Communication Signaling".IEEE Wireless Communications Letters 11.9(2022):1960-1964.
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