Integrated sensing and communication (ISAC) networks strive to deliver both high-precision target localization and high-throughput data services across the entire coverage area. In this work, we examine the fundamental trade-off between sensing and communication from the perspective of base station (BS) deployment. Furthermore, we conceive a design that simultaneously maximizes the target localization coverage, while guaranteeing the desired communication performance. In contrast to existing schemes optimized for a single target, an effective network-level approach has to ensure consistent localization accuracy throughout the entire service area. While employing time-of-flight (ToF) based localization, we first analyze the deployment problem from a localization-performance coverage perspective, aiming for minimizing the area Cramer-Rao Lower Bound (A-CRLB) to ensure uniformly high positioning accuracy across the service area. We prove that for a fixed number of BSs, uniformly scaling the service area by a factor κincreases the optimal A-CRLB in proportion to κ^{2β}, where βis the BS-to-target pathloss exponent. Based on this, we derive an approximate scaling law that links the achievable A-CRLB across the area of interest to the dimensionality of the sensing area. We also show that cooperative BSs extend the coverage but yield marginal A-CRLB improvement as the dimensionality of the sensing area grows.
翻译:集成感知与通信(ISAC)网络致力于在整个覆盖区域内同时提供高精度目标定位与高吞吐量数据服务。本文从基站(BS)部署的视角,探究感知与通信之间的基本权衡关系。进一步,我们提出一种设计,在保证期望通信性能的同时,最大化目标定位覆盖范围。与现有针对单一目标优化的方案不同,有效的网络级方法必须确保整个服务区域内定位精度的一致性。在采用基于飞行时间(ToF)的定位方法基础上,我们首先从定位性能覆盖的角度分析部署问题,旨在最小化区域克拉美-罗下界(A-CRLB),从而确保服务区域内均匀的高定位精度。我们证明,在基站数量固定的情况下,将服务区域均匀缩放κ倍会使最优A-CRLB按κ^{2β}比例增加,其中β为基站到目标的路径损耗指数。基于此,我们推导出一个近似缩放定律,将感兴趣区域内可实现的A-CRLB与感知区域的维度联系起来。我们还表明,协作基站能扩展覆盖范围,但随着感知区域维度的增加,其对A-CRLB的改善效果趋于有限。