ISAC Network Planning: Sensing Coverage Analysis and 3-D BS Deployment Optimization

TL;DR

This paper analyzes the trade-off between sensing and communication in ISAC networks, proposing a deployment strategy that maximizes localization coverage and guarantees communication performance using ToF-based localization and A-CRLB minimization.

Contribution

It introduces a network-level deployment approach optimizing localization accuracy and coverage, with a novel analysis of the impact of area scaling and cooperation among base stations.

Findings

Uniform area scaling increases A-CRLB proportionally to the square of the scale factor.

Cooperative BSs extend coverage but offer limited A-CRLB improvement in large sensing areas.

Derived an approximate scaling law linking A-CRLB to sensing area dimensionality.

Abstract

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 \kappa increases the optimal A-CRLB in proportion to \kappa^{2\beta}, where \beta is 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.