Digital-Twin Empowered Site-Specific Radio Resource Management in 5G Aerial Corridor

TL;DR

This paper introduces a digital-twin based resource management framework for drone corridor networks in 5G, improving throughput by leveraging high-fidelity channel information for optimized beamforming and association.

Contribution

It proposes a novel channel-twin enabled framework that enhances radio resource management in drone corridors through a two-stage optimization process.

Findings

Significant throughput improvements over baseline methods.

Effective use of digital-twin channel models for resource optimization.

Validated across diverse simulation scenarios.

Abstract

Base station (BS) association and beam selection in multi-cell drone corridor networks present unique challenges due to the high altitude, mobility and three-dimensional movement of drones. These factors lead to frequent handovers and complex beam alignment issues, especially in environments with dense BS deployments and varying signal conditions. To address these challenges, this paper proposes a channel-twin (CT) enabled resource-allocation framework for drone-corridor communications, where the CT constitutes the radio-channel component of a broader digital-twin (DT) environment. The CT supplies high-fidelity channel-state information (CSI), which drives a two-stage optimization procedure. In Stage 1, array-level beamforming weights at each BS are selected to maximize antenna gain. In Stage 2, the framework jointly optimizes drone-BS-beam associations at discrete corridor way-points to maximize end-to-end throughput. Simulation results confirm that the CT-driven strategy delivers significant throughput gains over baseline methods across diverse operating scenarios, validating the effectiveness of integrating precise digital-twin channel models with cross-layer resource optimization.