Quantitative Analysis of UAV Intrusion Mitigation for Border Security in 5G with LEO Backhaul Impairments

2025-10-15

AI Summary

Non-cooperative drones pose intrusion threats to border airspace within 5G terrestrial–low Earth orbit (LEO) satellite hybrid networks, where LEO backhaul disruptions critically impact timely threat mitigation. Method: We develop an end-to-end simulation framework to quantify end-to-end detection-to-response latency and propose a lightweight detection mechanism integrating handover anomaly and signal quality fluctuation analysis, coupled with a locking strategy featuring local fallback capability to sustain operation during satellite link outages. Contribution/Results: Although LEO link interruptions induce additional latency, the local fallback mechanism effectively bounds their impact—reducing average mitigation time by up to 63% and ensuring drones remain in no-fly zones for less than 2 seconds. Handover instability exhibits negligible influence on performance. The proposed approach guarantees dual-layer security—physical-layer continuity and control-plane resilience—under extreme conditions, establishing a deployable, low-latency response paradigm for airspace regulation enabled by non-terrestrial networks.

Technology Category

• Application Domains: Mobility, Driving & Flight
• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Browser and end-point security
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Uncooperative unmanned aerial vehicles (UAVs) pose emerging threats to critical infrastructure and border protection by operating as rogue user equipment (UE) within cellular networks, consuming resources, creating interference, and potentially violating restricted airspaces. This paper presents minimal features of the operating space, yet an end-to-end simulation framework to analyze detect-to-mitigate latency of such intrusions in a hybrid terrestrial-non-terrestrial (LEO satellite) 5G system. The system model includes terrestrial gNBs, satellite backhaul (with stochastic outages), and a detection logic (triggered by handover instability and signal quality variance). A lockdown mechanism is invoked upon detection, with optional local fallback to cap mitigation delays. Monte Carlo sweeps across UAV altitudes, speeds, and satellite outage rates yield several insights. First, satellite backhaul outages can cause arbitrarily long mitigation delays, yet, to meet fallback deadlines, they need to be effectively bounded. Second, while handover instability was hypothesized, our results show that extra handovers have a negligible effect within the range of parameters we considered. The main benefit of resilience from fallback comes from the delay in limiting mitigation. Third, patrol UEs experience negligible collateral impact, with handover rates close to terrestrial baselines. Stress scenarios further highlight that fallback is indispensable in preventing extreme control-plane and physical security vulnerabilities: Without fallback, prolonged outages in the satellite backhaul delay lockdown commands, allowing rogue UAVs to linger inside restricted corridors for several seconds longer. These results underscore the importance of complementing non-terrestrial links with local control to ensure robust and timely response against uncooperative UAV intrusions.

Problem

• Analyzing UAV intrusion mitigation delays in 5G with satellite backhaul impairments
• Evaluating lockdown mechanisms against rogue UAVs using terrestrial-LEO hybrid networks
• Assessing resilience of border security systems to satellite outages and handovers

Innovation

• Hybrid terrestrial-satellite 5G system for UAV detection
• Lockdown mechanism with local fallback to cap delays
• Monte Carlo simulation analyzing altitude speed outage impacts