Network-Level Analysis of Integrated Sensing and Communication Using Stochastic Geometry

Fuente: arXiv
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Autori principali: Wang, Ruibo, Belmekki, Baha Eddine Youcef, Zhang, Xue, Alouini, Mohamed-Slim
Natura: Preprint
Pubblicazione: 2024
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author Wang, Ruibo
Belmekki, Baha Eddine Youcef
Zhang, Xue
Alouini, Mohamed-Slim
author_facet Wang, Ruibo
Belmekki, Baha Eddine Youcef
Zhang, Xue
Alouini, Mohamed-Slim
contents To meet the demands of densely deploying communication and sensing devices in the next generation of wireless networks, integrated sensing and communication (ISAC) technology is employed to alleviate spectrum scarcity, while stochastic geometry (SG) serves as a tool for low-complexity performance evaluation. To assess network-level performance, there is a natural interaction between ISAC technology and the SG method. From ISAC network perspective, we illustrate how to leverage SG analytical framework to evaluate ISAC network performance by introducing point process distributions and stochastic fading channel models. From SG framework perspective, we summarize the unique performance metrics and research objectives of ISAC networks, thereby extending the scope of SG research in the field of wireless communications. Additionally, considering the limited discussion in the existing SG-based ISAC works in terms of distribution and channel modeling, a case study is designed to exploit topology and channel fading awareness to provide relevant network insights.
format Preprint
id arxiv_https___arxiv_org_abs_2404_13197
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Network-Level Analysis of Integrated Sensing and Communication Using Stochastic Geometry
Wang, Ruibo
Belmekki, Baha Eddine Youcef
Zhang, Xue
Alouini, Mohamed-Slim
Networking and Internet Architecture
To meet the demands of densely deploying communication and sensing devices in the next generation of wireless networks, integrated sensing and communication (ISAC) technology is employed to alleviate spectrum scarcity, while stochastic geometry (SG) serves as a tool for low-complexity performance evaluation. To assess network-level performance, there is a natural interaction between ISAC technology and the SG method. From ISAC network perspective, we illustrate how to leverage SG analytical framework to evaluate ISAC network performance by introducing point process distributions and stochastic fading channel models. From SG framework perspective, we summarize the unique performance metrics and research objectives of ISAC networks, thereby extending the scope of SG research in the field of wireless communications. Additionally, considering the limited discussion in the existing SG-based ISAC works in terms of distribution and channel modeling, a case study is designed to exploit topology and channel fading awareness to provide relevant network insights.
title Network-Level Analysis of Integrated Sensing and Communication Using Stochastic Geometry
topic Networking and Internet Architecture
url https://arxiv.org/abs/2404.13197