Cooperative Sensing and Communication for ISAC Networks: Performance Analysis and Optimization

In this work, we study integrated sensing and communication (ISAC) networks intending to effectively balance sensing and communication (S&C) performance at the network level. Through the simultaneous utilization of multi-point (CoMP) coordinated joint transmission and distributed multiple-input multiple-output (MIMO) radar techniques, we propose a cooperative networked ISAC scheme to enhance both S&C services. Then, the tool of stochastic geometry is exploited to capture the S&C performance, which allows us to illuminate key cooperative dependencies in the ISAC network. Remarkably, the derived expression of the Cramer-Rao lower bound (CRLB) of the localization accuracy unveils a significant finding: Deploying $N$ ISAC transceivers yields an enhanced sensing performance across the entire network, in accordance with the $\ln^2N$ scaling law. Simulation results demonstrate that compared to the time-sharing scheme, the proposed cooperative ISAC scheme can effectively improve the average data rate and reduce the CRLB.