In this study, we explore integrated sensing and communication (ISAC) networks to strike a more effective balance between sensing and communication (S&C) performance at the network scale. We leverage stochastic geometry to analyze the S&C performance, shedding light on critical cooperative dependencies of ISAC networks. According to the derived expressions of network performance, we optimize the user/target loads and the cooperative base station cluster sizes for S&C to achieve a flexible trade-off between network-scale S&C performance. It is observed that the optimal strategy emphasizes the full utilization of spatial resources to enhance multiplexing and diversity gain when maximizing communication ASE. In contrast, for sensing objectives, parts of spatial resources are allocated to cancel inter-cell sensing interference to maximize sensing ASE. Simulation results validate that the proposed ISAC scheme realizes a remarkable enhancement in overall S&C network performance.

翻译：本研究探索了集成感知与通信（ISAC）网络，旨在网络规模上实现感知与通信（S&C）性能间更有效的平衡。我们利用随机几何分析感知与通信性能，揭示了ISAC网络中关键的协作依赖关系。根据推导出的网络性能表达式，我们优化了用户/目标负载及通信与感知的协作基站簇规模，以实现网络级感知与通信性能的灵活权衡。研究发现，当最大化通信区域频谱效率（ASE）时，最优策略强调充分利用空间资源以增强复用与分集增益；相反，针对感知目标，部分空间资源被分配用于消除小区间感知干扰，以最大化感知ASE。仿真结果验证了所提出的ISAC方案在整体感知与通信网络性能上实现了显著提升。