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Intelligent Sensing and Communication assisted Pedestrians Recognition in Vehicular Networks: An Effective Throughput Maximization Approach
Yao Dengfeng1; Dai Minghui1; Wang Tianshun1; Wu Yuan1,2; Su Zhou3
2022-05
Conference NameIEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Source PublicationINFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops
Conference Date2022/05/02-2022/05/05
Conference PlaceNew York, NY, USA
Abstract

Intelligent vehicular network has been envisioned as an important paradigm of future pervasive intelligent networks in the sixth generation (6G) systems. To improve the efficiency of sensing and communication in future intelligent vehicular networks, the integrated sensing and communication (ISAC), which combines the communication and radar modules, has recently emerged as a promising scheme to improve spectrum efficiency by sharing bandwidth for radar sensing and data communication. In this paper, we investigate the intelligent ISAC for the scenario where the recognition targets are the same as the communication targets, namely, the vehicular transmitter firstly uses radar sensing to detect the potential pedestrian receivers and then sends data to those detected receivers. In particular, the sensing accuracy influences the consequent effective throughput to the detected users, which thus motivates us to formulate a joint allocation scheme of sensing-slot and transmission-duration for multi-user intelligent ISAC vehicular networks, with the objective of maximizing the overall effective throughput while ensuring the fairness among the target users. Despite the nature of mixed integer and non-convex programming problem, we propose a layered approach to solve the problem, in which we firstly optimize the transmission-durations under a given sensing-slot allocation. Then, we optimize the sensing-slot allocation by proposing an myopic allocation algorithm. Finally, we provide simulation results to validate the efficiency and effectiveness of our proposed algorithm, in comparison with some benchmark schemes.

DOI10.1109/INFOCOMWKSHPS54753.2022.9798291
Indexed ByCPCI-S
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000851573100147
Scopus ID2-s2.0-85133928257
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Citation statistics
Document TypeConference paper
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorWu Yuan
Affiliation1.State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China
2.Zhuhai UM Science & Technology Research Institute, Zhuhai, China
3.School of Cyber Science and Engineering, Xi’an Jiaotong University, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yao Dengfeng,Dai Minghui,Wang Tianshun,et al. Intelligent Sensing and Communication assisted Pedestrians Recognition in Vehicular Networks: An Effective Throughput Maximization Approach[C], 2022.
APA Yao Dengfeng., Dai Minghui., Wang Tianshun., Wu Yuan., & Su Zhou (2022). Intelligent Sensing and Communication assisted Pedestrians Recognition in Vehicular Networks: An Effective Throughput Maximization Approach. INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops.
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