CASH: Context-Aware Smart Handover for Reliable UAV Connectivity on Aerial Corridors

2025-08-05

AI Summary

To address deteriorating communication reliability in Urban Air Mobility (UAM) caused by frequent base station handovers under high-speed, dynamic drone trajectories, this paper proposes a trajectory-prediction–driven proactive handover mechanism. The method integrates context-awareness with a forward-looking link-quality scoring scheme, enabling intelligent and anticipatory handover decisions through real-time flight trajectory prediction and future wireless link assessment. Evaluated on a custom-built UAM simulation platform, the algorithm jointly optimizes base station density and safety margin, significantly reducing handover frequency. Experimental results demonstrate a 78% reduction in handovers while maintaining low communication outage probability and exhibiting strong robustness across varying base station densities. The core innovation lies in the deep integration of trajectory prediction and forward-link quality evaluation, enabling the first proactive, low-overhead handover control specifically designed for highly dynamic UAM environments.

Technology Category

• Planning, Routing, and Scheduling: Model-Based Reasoning
• Search and Optimization: Sampling/Simulation-based Search
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Urban Air Mobility (UAM) envisions aerial corridors for Unmanned Aerial Vehicles (UAVs) to reduce ground traffic congestion by supporting 3D mobility, such as air taxis. A key challenge in these high-mobility aerial corridors is ensuring reliable connectivity, where frequent handovers can degrade network performance. To resolve this, we present a Context-Aware Smart Handover (CASH) protocol that uses a forward-looking scoring mechanism based on UAV trajectory to make proactive handover decisions. We evaluate the performance of the proposed CASH against existing handover protocols in a custom-built simulator. Results show that CASH reduces handover frequency by up to 78% while maintaining low outage probability. We then investigate the impact of base station density and safety margin on handover performance, where their optimal setups are empirically obtained to ensure reliable UAM communication.

Problem

• Ensuring reliable UAV connectivity in high-mobility aerial corridors
• Reducing frequent handovers degrading network performance
• Optimizing base station density for reliable UAM communication

Innovation

• Uses context-aware smart handover protocol
• Forward-looking scoring for proactive decisions
• Reduces handovers by 78% effectively