Joint Sensing and Communications Using Bi-static Radar With Two Users

Joint sensing and communications (JSAC) systems have garnered significant research attention by integrating sensing capabilities with communication functionalities. Despite this interest, there is limited exploration of scenarios involving multiple users. This paper addresses this problem by investigating a dual-user JSAC system, with a focus on user interference and optimal performance trade-offs through a time-division approach. The sum rate, detection probability and their mixture are evaluated. The results show that the system performance can be optimized via time division. This research underscores the advantages of time-division strategies and the inclusion of multiple users in JSAC systems.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icct62411.2024.10946614
Primary Topic
Distributed Sensor Networks and Detection Algorithms
Type
article
Field-Weighted Citation Impact
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article

Joint Sensing and Communications Using Bi-static Radar With Two Users

Yun Xiao, Enhao Wang, Yunfei Chen
Distributed Sensor Networks and Detection Algorithms
article

Joint Sensing and Communications Using Bi-static Radar With Two Users

Yun Xiao, Enhao Wang, Yunfei Chen
article en

Abstract

Joint sensing and communications (JSAC) systems have garnered significant research attention by integrating sensing capabilities with communication functionalities. Despite this interest, there is limited exploration of scenarios involving multiple users. This paper addresses this problem by investigating a dual-user JSAC system, with a focus on user interference and optimal performance trade-offs through a time-division approach. The sum rate, detection probability and their mixture are evaluated. The results show that the system performance can be optimized via time division. This research underscores the advantages of time-division strategies and the inclusion of multiple users in JSAC systems.

Durham University (GB)
Affordable and clean energy
Openalex Percentile: Top 65%
Distributed Sensor Networks and Detection Algorithms
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