Unmanned Aerial Vehicles for Non-Terrestrial Communications and Sensing

Informazioni relative al progetto

UNITE

ID dell’accordo di sovvenzione: 101129618

DOI

10.3030/101129618

Data della firma CE 13 Ottobre 2023

Data di avvio 1 Dicembre 2023

Data di completamento 30 Novembre 2027

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 496 800,00

Coordinato da

UNIVERSITA DEGLI STUDI DI PADOVA
Italy

Periodic Reporting for period 1 - UNITE (Unmanned Aerial Vehicles for Non-Terrestrial Communications and Sensing)

Periodo di rendicontazione: 2023-12-01 al 2025-11-30

Sintesi del contesto e degli obiettivi generali del progetto

Europe is investing heavily in next-generation communication systems (6G) to ensure secure, resilient, and sustainable connectivity for all citizens. However, traditional terrestrial networks alone cannot guarantee reliable coverage in rural, remote, maritime, or disastered areas. At the same time, new services such as environmental monitoring, smart mobility, emergency response, and immersive applications require not only communication but also advanced sensing capabilities. The UNITE project addresses these challenges by exploring how unmanned aerial vehicles (UAVs), in combination with satellites, can support and integrate advanced non-terrestrial communications (NTC) and non-terrestrial sensing (NTS) in 6G, to reduce digital inequality, increase network flexibility and robustness, and improve situational awareness in critical scenarios.

In this context, the objectives of the UNITE project are to:
- Design intelligent, data-driven, and adaptive UAV deployment strategies based on realistic spatial/temporal traffic patterns and environmental information.
- Build new realistic and robust channel, interference, and sensing models to describe the 3D environment for both NTC and NTS;
- Develop efficient data transmission strategies (for NTC) to ensure the reliable delivery of information, and the accurate and timely acquisition of network perception (for NTS) using new channel models, metasurface/RIS systems, and computer vision.
- Develop new algorithms and signal-processing techniques to integrate NTC and NTS, using dual-functional waveforms and UAV wireless charging.
- Design effective sensing-based communications using UAVs for integrated NTC and NTS.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

During RP1, the project achieved significant scientific and technical progress across all WPs.

-Data-driven analysis of spatial and temporal traffic demands in representative 6G NTC scenarios. Traffic hotspots and environment types have been automatically identified from GIS data, satellite imagery, and operator traffic traces using machine-learning-based semantic segmentation and clustering techniques. These spatial-temporal predictions will be used to identify where UAVs should be positioned, based on where traffic demand is expected to increase.
- Realistic 3D channel and sensing models for both NTC and NTS combining deterministic ray-tracing, measurement-driven simulations, mathematical methods, and machine-learning-assisted stochastic models. The resulting models capture different UAV altitudes, mobility patterns, channel conditions, as well as clutter, Doppler, delay spread, and multi-path effects for sub-6 GHz, mmWave, and sub-THz bands.
- Efficient standalone designs for NTC and NTS. For communications, reliable transmission strategies have been evaluated using the newly established channel models. In parallel, UAV-assisted sensing designs have exploited bi-static UAV-ground geometries, mobility-aware waveform selection, metasurface/RIS systems, and computer-vision perception data to accurately characterize targets and environments.
- Algorithms and signal-processing techniques for integrated NTC and NTS. Dual-functional ISAC waveforms and beamforming strategies have been designed to jointly satisfy communication and sensing performance requirements in mixed near- and far-field scenarios, possibly using RIS systems. The results have demonstrated the feasibility of robust NTC-NTS ISAC operations.
- Sensing-assisted communication. Early designs have demonstrated how UAV-based sensing information can be exploited to enhance communication decisions, for example adapt beamforming, resource allocation, scheduling, and handover in integrated NTC-NTS systems, laying the groundwork for closed-loop sensing-driven communication architectures to be completed in the second half of the project.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

In RP1, the project has advanced the state of the art in several important ways.
- The project moves beyond a traditional two-dimensional and static network design by introducing realistic three-dimensional, mobility-aware channel, interference, and sensing models for UAV- and satellite-based systems. These models capture air-to-ground, air-to-air, and air-to-space propagation under dynamic conditions, and incorporate environmental features, multi-path components, Doppler dynamics, and frequency-dependent effects for multiple bands. This enables more accurate system design in complex urban and rural environments.
- The project goes beyond treating communication and sensing as separate functions. Rather, it develops integrated NTC and NTS architectures, including dual-functional waveforms, as well as sensing-assisted beamforming, resource allocation, scheduling and handover. These solutions demonstrate how sensing outputs (such as Doppler/scattering fingerprints and clutter awareness) can be directly exploited to enhance communication performance, as well as improve target detection and prediction accuracy. The project also explores the use metasurface and RIS systems to support integrated sensing and communications (ISAC) in realistic deployments, for example improving security and authentication.
- The project introduces data-driven UAV deployment strategies based on machine learning, semantic environmental classification, and traffic clustering. This allows UAVs to be deployed proactively where demand is expected to increase, rather than reactively after congestion occurs.

The research activities planned for RP2 will build upon the solid scientific and technological foundations achieved in RP1. To ensure effective exploitation of the project results, several complementary actions are foreseen, included: (i) proper validation of the proposed technological solutions through full proof-of-concept demonstrations; (ii) active contributions to standardization bodies (e.g. 3GPP and ITU); and (iii) closer engagement with industry and SMEs to assess the innovation and market potential of the project’s ideas, with a view to protecting key results through patent applications (IPR) where appropriate, and ensure that research activities remain aligned with real-world constraints, industrial practices and future market needs and use cases.

Schematic representation of the project's activities