Sensing Performance Analysis in Cooperative Air-Ground ISAC Networks for LAE

2025-10-03

AI Summary

Accurately evaluating sensing performance—particularly regional radar detection coverage probability—remains challenging for air-ground cooperative Integrated Sensing and Communication (ISAC) networks in low-altitude economy scenarios, especially under constant false alarm rate constraints. Method: To capture realistic interference characteristics in ultra-dense picocell environments, this work proposes a stochastic geometry-based multi-source interference statistical model, moving beyond conventional simplifications that consider only the dominant interferer. A closed-form analytical expression for coverage probability is derived rigorously. Contribution/Results: Simulation results validate the model’s high prediction accuracy under dense base station deployments. The proposed framework significantly improves the accuracy of detection coverage probability estimation, thereby providing a quantifiable, theoretically grounded basis for ISAC network deployment and coordinated interference management in low-altitude economy applications.

Technology Category

• Reasoning under Uncertainty: Stochastic Optimization
• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Intelligent Robots: State Estimation

Application Category

• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

To support the development of low altitude economy, the air-ground integrated sensing and communication (ISAC) networks need to be constructed to provide reliable and robust communication and sensing services. In this paper, the sensing capabilities in the cooperative air-ground ISAC networks are evaluated in terms of area radar detection coverage probability under a constant false alarm rate, where the distribution of aggregated sensing interferences is analyzed as a key intermediate result. Compared with the analysis based on the strongest interferer approximation, taking the aggregated sensing interference into consideration is better suited for pico-cell scenarios with high base station density. Simulations are conducted to validate the analysis.

Problem

• Analyzing sensing performance in cooperative air-ground ISAC networks
• Evaluating radar detection coverage probability under false alarm constraints
• Modeling aggregated interference effects for high-density base station scenarios

Innovation

• Analyzing aggregated sensing interference distribution for performance
• Evaluating radar detection coverage under constant false alarm rate
• Optimizing pico-cell scenarios with high base station density