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：本文研究集成感知与通信（ISAC）网络，旨在网络层面有效平衡感知与通信（S&C）性能。通过同时利用多点协作（CoMP）协调联合传输与分布式多输入多输出（MIMO）雷达技术，我们提出一种协同网络化ISAC方案以增强S&C服务。进而采用随机几何工具捕捉S&C性能，从而揭示ISAC网络中关键的协同依赖关系。值得注意的是，定位精度的克拉美-罗下界（CRLB）推导表达式揭示了一个重要发现：部署$N$个ISAC收发器可提升整个网络的感知性能，且满足$\ln^2N$标度律。仿真结果表明，相较于时间共享方案，所提出的协同ISAC方案能有效提升平均数据速率并降低CRLB。