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.

翻译：本文研究感知与通信一体化网络，旨在网络层面有效平衡感知与通信性能。通过协同多点联合传输与分布式多输入多输出雷达技术的同步利用，我们提出一种协同网络化ISAC方案以增强感知与通信服务。随后，利用随机几何工具刻画感知与通信性能，这使我们能够阐明ISAC网络中的关键协同依赖关系。值得注意的是，所推导的定位精度克拉美-罗下界表达式揭示了一个重要发现：部署$N$个ISAC收发器能够依据$\ln^2N$缩放律提升全网感知性能。仿真结果表明，与时分方案相比，所提出的协同ISAC方案能够有效提升平均数据速率并降低CRLB。