2025/11/17 by Niccolò Paglierani, Paglierani, Niccolò, Francesco Linsalata +7
Engineering · #Air Traffic Management and Optimization #FOS: Electrical engineering #Indoor and Outdoor Localization Technologies #Signal Processing (eess.SP) #UAV Applications and Optimization #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2511.13171
openalex publication_date 2025/11/17 · openalex created_date 2025/11/19 · openalex updated_date 2026/08/01
This paper presents an autonomous sensing framework for identifying and localizing multiple User Equipments (UEs) in Fifth Generation (5G) cellular networks using a non-serving Unmanned Aerial Vehicle (UAV). A complete onboard processing chain is developed to perform synchronization, multi-UE identification, and localization directly from standard 3GPP-compliant uplink Sounding Reference Signals (SRS). Unlike conventional UAV-assisted approaches relying on serving nodes or infrastructure support, the proposed platform operates as a passive sensing UAV, requiring only limited initial coordination with the network and no mission-time control-plane interaction. The approach exploits the structured and periodic nature of SRS transmissions together with a tailored protocol configuration to ensure robust operation under realistic multi-UE interference. The system operates with narrowband SRS (1.4 MHz), reducing UE power consumption and hardware complexity while enabling high multiplexing through cyclic shifts and frequency resources. Reliable synchronization and multi-UE identification are achieved even when multiple UEs share the same resources. The UAV autonomously collects measurements along its trajectory and estimates UE positions using a trajectory-based localization strategy. The proposed framework is validated through extensive simulations and a full-scale experimental campaign, achieving localization errors below 8 m in urban scenarios and below 3 m in rural conditions, outperforming state-of-the-art Angle of Arrival (AoA)- and Time Difference of Arrival (TDoA)-based methods by about 5-6 m. These results demonstrate the feasibility of infrastructure-independent sensing UAVs for Low-Altitude Wireless Networks (LAWN), enabling scalable and rapidly deployable situational awareness in emergency and connectivity-limited environments.