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ISAC network planning: sensing coverage analysis and 3-D BS deployment optimization

ISAC network planning: sensing coverage analysis and 3-D BS deployment optimization
ISAC network planning: sensing coverage analysis and 3-D BS deployment optimization
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 Cramér-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 κ increases the optimal A-CRLB in proportion to κ2β, where β 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. By exploiting the invariance properties discovered with respect to the displacement, rotation, and symmetric projection deformation, we derive a deployment-invariant structure for conceiving a low complexity framework for ISAC network deployment. We then formulate the joint sensing-communication optimization problem and present a Majorization-Minimization algorithm for designing high-quality deployment solutions. Extensive simulations demonstrate that our framework significantly enhances sensing coverage, while maintaining the desired communication throughput.
1536-1276
Meng, Kaitao
98f41982-3656-4095-9e67-b576f078fd52
Han, Kawon
afa3b753-493d-4f72-8dd3-65a46c2e239a
Masouros, Christos
76e33f94-b9d9-4f7d-85b7-924dc26942d5
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Liu, Xin
18299dbd-af76-4728-ac01-76eb68b2d76a
Meng, Kaitao
98f41982-3656-4095-9e67-b576f078fd52
Han, Kawon
afa3b753-493d-4f72-8dd3-65a46c2e239a
Masouros, Christos
76e33f94-b9d9-4f7d-85b7-924dc26942d5
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Meng, Kaitao, Han, Kawon, Masouros, Christos and Hanzo, Lajos (2025) ISAC network planning: sensing coverage analysis and 3-D BS deployment optimization. IEEE Transactions on Wireless Communications. (In Press)

Record type: Article

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 Cramér-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 κ increases the optimal A-CRLB in proportion to κ2β, where β 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. By exploiting the invariance properties discovered with respect to the displacement, rotation, and symmetric projection deformation, we derive a deployment-invariant structure for conceiving a low complexity framework for ISAC network deployment. We then formulate the joint sensing-communication optimization problem and present a Majorization-Minimization algorithm for designing high-quality deployment solutions. Extensive simulations demonstrate that our framework significantly enhances sensing coverage, while maintaining the desired communication throughput.

Text
Final Paper-TW-Jun-25-1486.R1 - Accepted Manuscript
Restricted to Repository staff only until 9 March 2026.
Available under License Creative Commons Attribution.
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More information

Accepted/In Press date: 22 December 2025

Identifiers

Local EPrints ID: 508992
URI: http://eprints.soton.ac.uk/id/eprint/508992
ISSN: 1536-1276
PURE UUID: c8e3b431-754f-48d2-a0c1-6537110815b7
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 09 Feb 2026 17:57
Last modified: 10 Feb 2026 02:33

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Contributors

Illustrator: Xin Liu
Author: Kaitao Meng
Author: Kawon Han
Author: Christos Masouros
Author: Lajos Hanzo ORCID iD

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