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

TL;DR

This paper explores how stochastic geometry can be used to evaluate the performance of integrated sensing and communication networks, addressing spectrum scarcity in future wireless systems.

Contribution

It introduces a framework combining stochastic geometry with ISAC network analysis, extending existing models with new distribution and channel considerations.

Findings

Developed a stochastic geometry-based analytical framework for ISAC networks.

Provided insights into topology and channel fading effects on network performance.

Extended stochastic geometry applications to include ISAC-specific metrics.

Abstract

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.