Residential College | false |
Status | 已發表Published |
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 Name | IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) |
Source Publication | INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops |
Conference Date | 2022/05/02-2022/05/05 |
Conference Place | New 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. |
DOI | 10.1109/INFOCOMWKSHPS54753.2022.9798291 |
Indexed By | CPCI-S |
WOS Research Area | Computer Science ; Engineering ; Telecommunications |
WOS Subject | Computer Science, Information Systems ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications |
WOS ID | WOS:000851573100147 |
Scopus ID | 2-s2.0-85133928257 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) |
Corresponding Author | Wu Yuan |
Affiliation | 1.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 Affilication | University of Macau |
Corresponding Author Affilication | University 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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