Performance Analysis of Clustered Integrated Sensing and Communication Networks

Integrated sensing and communication (ISAC) provides a promising approach for IoT networks by combining data transmission with target sensing over shared hardware. Different from prior studies centered on the performance of ISAC networks with uniformly distributed nodes, this work explores ISAC networks with clustered distributed nodes. An analytical model based on stochastic geometry is established to assess both the probabilities of sensing and communication in clustered ISAC networks. The study highlights the influence of factors such as cluster density, node distribution, and cluster size on both sensing and communication performance. Simulations validate the accuracy of the proposed model and demonstrate that fine-tuning cluster parameters can significantly improve the performance of clustered ISAC networks.