Back to Search Start Over

Integrated sensing and communication based outdoor multi-target detection, tracking, and localization in practical 5G Networks

Authors :
Ruiqi Liu
Mengnan Jian
Dawei Chen
Xu Lin
Yichao Cheng
Wei Cheng
Shijun Chen
Source :
Intelligent and Converged Networks, Vol 4, Iss 3, Pp 261-272 (2023)
Publication Year :
2023
Publisher :
Tsinghua University Press, 2023.

Abstract

The 6th generation (6G) wireless networks will likely to support a variety of capabilities beyond communication, such as sensing and localization, through the use of communication networks empowered by advanced technologies. Integrated sensing and communication (ISAC) has been recognized as a critical technology as well as a usage scenario for 6G, as widely agreed by leading global standardization bodies. ISAC utilizes communication infrastructure and devices to provide the capability of sensing the environment with high resolution, as well as tracking and localizing moving objects nearby. Meeting both the requirements for communication and sensing simultaneously, ISAC-based approaches celebrate the advantages of higher spectral and energy efficiency compared to two separate systems to serve two purposes, and potentially lower costs and easy deployment. A key step towards the standardization and commercialization of ISAC is to carry out comprehensive field trials in practical networks, such as the 5th generation (5G) networks, to demonstrate its true capacities in practical scenarios. In this paper, an ISAC-based outdoor multi-target detection, tracking and localization approach is proposed and validated in 5G networks. The proposed system comprises of 5G base stations (BSs) which serve nearby mobile users normally, while accomplishing the task of detecting, tracking, and localizing drones, vehicles, and pedestrians simultaneously. Comprehensive trial results demonstrate the relatively high accuracy of the proposed method in practical outdoor environment when tracking and localizing single targets and multiple targets.

Details

Language :
English
ISSN :
27086240
Volume :
4
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Intelligent and Converged Networks
Publication Type :
Academic Journal
Accession number :
edsdoj.31d8641ff4446e861b7051fa78cf71
Document Type :
article
Full Text :
https://doi.org/10.23919/ICN.2023.0021