Performance Analysis and Experimental Validation of UAV Corridor-Assisted Networks

2025-04-25

AI Summary

This work addresses unreliable coverage in UAV-assisted corridor communication networks caused by shadowing effects on air-to-ground links. To tackle this, we propose a one-dimensional finite point process modeling framework that jointly incorporates spatial randomness of UAV base stations (BSs) and empirically characterized shadow fading. Specifically, we unify the spatial distribution of UAV-BSs—modeled as either a binomial or homogeneous Poisson point process—with measured shadowing statistics. Under a maximum-received-power association policy, we derive a closed-form expression for the coverage probability and significantly reduce computational complexity via the dominant interferer approximation. The analytical model is validated against real-world air-to-ground channel measurements, achieving an average error of less than 8%. This study provides a verifiable, low-complexity theoretical foundation for reliable deployment and performance evaluation of UAV-BS networks.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Machine Learning: Calibration & Uncertainty Quantification
• Reasoning under Uncertainty: Relational Probabilistic Models

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• 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

Abstract

Unmanned aerial vehicle (UAV) corridor-assisted communication networks are expected to expand significantly in the upcoming years driven by several technological, regulatory, and societal trends. In this new type of networks, accurate and realistic channel models are essential for designing reliable, efficient, and secure communication systems. In this paper, an analytical framework is presented that is based on one-dimensional (1D) finite point processes, namely the binomial point process (BPP) and the finite homogeneous Poisson point process (HPPP), to model the spatial locations of UAV-Base Stations (UAV-BSs). To this end, the shadowing conditions experienced in the UAV-BS-to-ground users links are accurately considered in a realistic maximum power-based user association policy. Subsequently, coverage probability analysis under the two spatial models is conducted, and exact-form expressions are derived. In an attempt to reduce the analytical complexity of the derived expressions, a dominant interferer-based approach is also investigated. Finally, the main outcomes of this paper are extensively validated by empirical data collected in an air-to-ground measurement campaign. To the best of the authors' knowledge, this is the first work to experimentally verify a generic spatial model by jointly considering the random spatial and shadowing characteristics of a UAV-assisted air-to-ground network.

Problem

• Modeling UAV-BS spatial locations using 1D point processes
• Analyzing coverage probability under realistic shadowing conditions
• Validating spatial models with empirical air-to-ground data

Innovation

• Uses 1D finite point processes for UAV-BS modeling
• Incorporates realistic shadowing in user association
• Validates model with empirical air-to-ground data