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

Integrated sensing and communication (ISAC) is a promising technology for next-generation wireless networks, enabling applications that require enhanced communication and precise sensing capabilities. Notable examples include smart environments, augmented and virtual reality, and the internet of things, where the functionalities of intelligent sensing and broadband communications are paramount. Consequently, ISAC has attracted significant research interest from academia and industry, resulting in numerous investigations conducted over the past decade. The literature encompasses a diverse range of articles, including system models, performance evaluations, and optimization studies of various ISAC designs. Stochastic geometry (SG) is the study of random spatial patterns. As such, SG tools have been used to evaluate the performance of wireless networks with different types of nodes. In this paper, we present a comprehensive survey of current research on the performance evaluation of ISAC systems that employ SG tools. The survey covers terrestrial, aerial, and vehicular networks, addressing the random spatial location of network elements, propagation scatterers, and blockages through various point processes. The paper begins with an overview of ISAC technology, SG tools, and performance evaluation metrics for communication and sensing. Next, we elaborate on the technical components of the system models employed in the surveyed literature. Then, we present pertinent literature findings across diverse network types using three levels of integration: sensing-assisted communication, communication-assisted sensing, and collaborative sensing and communication. Lastly, we discuss the challenges and potential directions of forthcoming research.