Stochastic Geometry for Modeling and Analysis of Sensing and Communications: A Survey

TL;DR

This survey demonstrates how stochastic geometry enables tractable, large-scale evaluation of integrated sensing and communication (ISAC) networks across terrestrial, aerial, and vehicular scenarios. It introduces fundamental SG models and key ISAC metrics, then surveys system models and results for ISAC, JCAS, and SAC, highlighting how node distributions (e.g., PPP, MCP, DPP) and integration levels shape coverage, rate, and sensing performance. The paper underscores design trade-offs (density, beamwidth, resource allocation) and the potential of RIS and cooperative sensing, while outlining open problems—novel point processes, EM/ESIT considerations, extended metrics, SG–AI hybrids, and heterogeneous technologies—for advancing SG-based ISAC research. Collectively, the work provides a roadmap for rigorous, geometry-driven analysis that informs practical 6GISAC deployments and standardization efforts by linking spatial randomness to measurable performance gains.

Abstract

One of the most promising technologies for next-generation wireless networks is integrated communication and sensing (ISAC). It is considered a key enabler for applications that require both enhanced communication and accurate sensing capabilities. Examples of such applications include smart environments, augmented and virtual reality, or the internet of things, where the capabilities of intelligent sensing and broadband communications are vital. Therefore, ISAC has attracted the research interest of both academia and industry, and many investigations have been carried out over the past decade. The articles in the literature include system models, performance evaluation, and optimization studies of several ISAC alternative designs. Stochastic geometry is the study and analysis of random spatial patterns, and as such, stochastic geometry tools have been considered for the performance evaluation of wireless networks with different types of nodes. In this paper, we aim to provide a comprehensive survey of current research progress in performance evaluation of ISAC systems using stochastic geometry tools. The survey covers terrestrial, aerial, and vehicular networks, where the random spatial location of the corresponding network elements and propagation scatterers and/or blockages is treated with various point processes. The paper starts with a short tutorial on ISAC technology, stochastic geometry tools, and metrics used in performance evaluation of communication and sensing. Then, the technical components of the system models utilized in the surveyed papers are discussed. Subsequently, we present the key results of the literature in all types of networks using three levels of integration: sensing-assisted communication, communication-assisted sensing, and joint sensing and communication. Finally, future research challenges and promising directions are discussed.

Figures (5)

• Figure 1: The structure of the paper.
• Figure 2: Realizations of point processes for communication and sensing networks.
• Figure 3: Types and configurations of sensing and communication networks.
• Figure 5: Future directions.
• Figure 6: Conceptualization of a unified SG-based framework for communication and sensing networks.