Large-Scale Wireless Networks for the ISCC: Spatial Modeling and Performance Analysis

Integrated sensing, communication, and computation (ISCC) networks have emerged as a key enabler for intelligent applications. Most existing works focus on small-scale ISCC systems with a limited number of nodes, making it difficult to provide guidance for large-scale ISCC network design. This paper bridges this gap by developing an analytical framework for large-scale ISCC networks with massive spatially random distributed nodes, in which both periodic requests and aperiodic requests are considered. To support dynamic sensing requests, integrated sensing and communication (ISAC) devices perform wireless sensing to collect sensing data, which will be processed through either edge offloading or local computing. Given the model, the queue dynamics and interference intensity are first analyzed for interference characterization. Next, the b-th moments and the meta distribution of successful sensing probability and successful communication probability are derived. Based on these results, the sensing delay, communication delay, and computing delay are jointly analyzed to evaluate the end to end (E2E) delay performance. Simulation results validate the accuracy of the proposed analytical framework in terms of ISAC service reliability and E2E delay. It shows that compared with the benchmark analytical frameworks that underestimate delay, the proposed framework provides accurate performance characterization to avoid unreliable network deployment. Further, the impact of network parameters on delay performance and the tradeoffs between sensing reliability and E2E delay, communication reliability and E2E delay, as well as local and edge computing delays, is numerically analyzed. These results can provide useful insights to enable appropriate system design based on multiple performance metrics.