TITAN: Twin-Informed Topology Adaptation for LAWN-enabled D2C Communication

2026-02-28

AI Summary

This study addresses the unreliability of satellite-to-ground direct communication in dense urban environments, where signal blockage often compromises post-disaster connectivity. To overcome this challenge, the authors propose leveraging unmanned aerial vehicles (UAVs) within a low-altitude wireless network (LAWN) as adaptive aerial relays for direct-to-cellular (D2C) links. The work innovatively integrates high-fidelity digital twins with Sionna-based ray-tracing channel modeling and employs Bayesian optimization to dynamically configure the relay topology, thereby surpassing the limitations of conventional heuristic or statistical channel approaches. System-level simulations demonstrate significant performance gains over existing methods, including a 32.2% improvement in user coverage, a 64.9% increase in aggregate system throughput, and a 49.3% enhancement in fairness.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Low-Altitude Wireless Networks (LAWN) are transforming the low-altitude airspace into a mission-driven, dynamically reconfigurable 3D network fabric for safety-critical and public-safety operations. In parallel, Direct-to-Cell (D2C) satellite access can rapidly restore connectivity after disasters, yet dense urban blockages make the satellite-to-ground link unreliable for many users. To overcome this, we leverage the LAWN aerial layer and form an adaptive low-altitude relay topology where Unmanned Aerial Vehicles (UAVs) act as D2C-assisted aerial relays for obstructed ground users. We introduce TITAN, a twin-informed topology adaptation framework that builds a high-fidelity Digital Twin (DT) of the affected urban area and performs site-specific, ray-traced air-to-ground channel modeling via Sionna RT. This informs a Bayesian optimization process that adapts the aerial topology to maximize coverage and Quality of Service (QoS) for ground users by using UAVs as optimal D2C relays. Extensive system-level simulations with Sionna show that TITAN consistently outperforms the baselines and delivers +32.2% user coverage, +64.9% system sum-rate, and +49.3% fairness over the state-of-the-art (SOTA) that employ heuristic placement or statistical channel approximations. To support further research in resilient network design, we open-source the codebase of the TITAN framework.

Problem

• Low-Altitude Wireless Networks
• Direct-to-Cell
• Urban Blockage
• Aerial Relays
• Coverage

Innovation

• Digital Twin
• Bayesian Optimization
• Ray-Traced Channel Modeling
• UAV Relay
• LAWN