Network-level ISAC: Performance Analysis and Optimal Antenna-to-BS Allocation

2024-10-08

arXiv.org

AI Summary

This work investigates the impact of antenna topology—ranging from massive MIMO to cell-free MIMO—on joint sensing and communication performance in integrated sensing and communication (ISAC) networks, focusing on antenna–base station allocation strategies and trade-offs among beamforming gain, coherent processing, diversity, and coverage under geographically centralized versus distributed architectures. We propose a network-level ISAC architecture unifying coordinated multipoint (CoMP) communication with multistatic sensing. For the first time, we derive fundamental scaling laws for time-of-flight (TOF), angle-of-arrival (AOA), and hybrid localization accuracy as ln²N, ln N, and a ln²N + b ln N, respectively; further proving that the path-loss exponent dictates the optimal spatial antenna distribution. Leveraging Poisson point process modeling, Cramér–Rao bound analysis, and cooperative region characterization, we obtain closed-form expressions for localization accuracy scaling and communication rate, and establish an antenna allocation optimization criterion balancing sensing precision and communication gain.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Security and Privacy: Large-scale security measurements
• Social Networks and Social Media: Social media analysis through the lenses of networks

Abstract

A cooperative architecture is proposed for integrated sensing and communication (ISAC) networks, incorporating coordinated multi-point (CoMP) transmission along with multi-static sensing. We investigate how the allocation of antennas-to-base stations (BSs) affects cooperative sensing and cooperative communication performance. More explicitly, we balance the benefits of geographically concentrated antennas, which enhance beamforming and coherent processing, against those of geographically distributed antennas, which improve diversity and reduce service distances. Regarding sensing performance, we investigate three localization methods: angle-of-arrival (AOA)-based, time-of-flight (TOF)-based, and a hybrid approach combining both AOA and TOF measurements, for critically appraising their effects on ISAC network performance. Our analysis shows that in networks having N ISAC nodes following a Poisson point process, the localization accuracy of TOF-based methods follow a ln^2 N scaling law (explicitly, the Cram'er-Rao lower bound (CRLB) reduces with ln^2 N). The AOA-based methods follow a ln N scaling law, while the hybrid methods scale as aln^2 N + bln N, where a and b represent parameters related to TOF and AOA measurements, respectively. The difference between these scaling laws arises from the distinct ways in which measurement results are converted into the target location. In terms of communication performance, we derive a tractable expression for the communication data rate, considering various cooperative region sizes and antenna-to-BS allocation strategy. It is proved that higher path loss exponents favor distributed antenna allocation to reduce access distances, while lower exponents favor centralized antenna allocation to maximize beamforming gain.

Problem

• Analyzes antenna allocation impact on ISAC network performance
• Compares massive MIMO vs cell-free MIMO for sensing/communication
• Evaluates AOA, TOF, and hybrid localization methods in ISAC

Innovation

• CoMP transmission with multi-static sensing
• Massive MIMO vs cell-free antenna allocation
• Hybrid AOA-TOF localization scaling analysis