Modeling and Performance Analysis for Clustered Integrated Sensing and Communication Networks
Yixiao Gu, Jian He, Yinghong Guo, Bin Xia, Dan Zeng · IEEE Transactions on Wireless Communications · 2025
The stochastic geometry-based modeling and analysis of large-scale Integrated Sensing and Communication (ISAC) networks are vital for providing useful ISAC design insights. One important ISAC network characteristic is the sensing and communication (S&C) spatial correlations since the communication users (CUs) are more interested in the sensing target (STs) around them and the base stations prefer to utilize one ISAC signal to serve the CUs and STs close to each other to enable effective S&C coverage. However, most existing works focused on ISAC systems where the locations of CUs and STs are assumed to be independent. This paper bridges this gap by proposing an analytical framework for the ISAC networks where the unified ISAC waveform is modeled with limited main lobe beamwidth and the CUs and STs served by one signal are assumed to be correlatively distributed in spatial domain. Given the model, we first derive some prerequisite auxiliary quantities (i.e., the probability that an ST is served by the main lobe or side lobe, the link distance distribution, etc.) to analyze the network characteristics. Further, the communication/sensing coverage probability, as well as the joint and conditional ISAC coverage probability are analyzed to provide the comprehensive analysis results. Combining the theoretical analysis and simulation results, it verifies the accuracy of the analytical framework and quantifies the impact of the network parameters and spatial correlations on the S&C performance. Moreover, our results reveal how the sensing performance and communication performance are mutually restricted to describe the tradeoffs of S&C performance.