TITAN: Twin-Informed Topology Adaptation for LAWN-enabled D2C Communication
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866914361354747904 |
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| author | Sarı, Talip Tolga Ahmed, Rameez Noman, Abdullah Al Seçinti, Gökhan Dick, Chris Roy, Debashri |
| author_facet | Sarı, Talip Tolga Ahmed, Rameez Noman, Abdullah Al Seçinti, Gökhan Dick, Chris Roy, Debashri |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_00795 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | TITAN: Twin-Informed Topology Adaptation for LAWN-enabled D2C Communication Sarı, Talip Tolga Ahmed, Rameez Noman, Abdullah Al Seçinti, Gökhan Dick, Chris Roy, Debashri Networking and Internet Architecture 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. |
| title | TITAN: Twin-Informed Topology Adaptation for LAWN-enabled D2C Communication |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2603.00795 |