AirLoc: A QoS-aware Mobile Location Service Framework via UAV-assisted LoRa Networks

As the demand for Location-Based Services (LBS) grows in remote or resource-limited regions, providing high Quality of Service (QoS) location for wide mobile applications has become increasingly crucial. Existing approaches typically rely on fixed gateways and static nodes, which is unsuitable or expensive in demanding environments such as wild fields or temporary sites. In this paper, we propose AirLoc, a QoS aware framework that ensures long-range, accurate, and low cost location services for wide mobile scenarios. Considering that LoRa (Long Range) is suitable for localization in wide areas due to its long-range and low-power nature. AirLoc uses only one single legacy UAV-assisted LoRa gateway to track mobile LoRa targets without relying on dense infrastructure. AirLoc is mainly based on the key observation that LoRa's RSSI is insensitive at long ranges and unstable at short ranges. To address these issues, we propose three key service modules for AirLoc framework. We first propose a LoRa spreading factor-based long range localization module to determine the coarse region of the targets. Additionally, we design an RSSI reconstruction–based module to achieve accurate tracking in short ranges. Finally, a QoS-driven interaction protocol module is used to operate the architecture with minimal overhead. We implement AirLoc on both a real-world testbed that includes a UAV-assisted LoRa gateway and a large-scale simulation platform. Extensive real world experiments show that AirLoc accurately tracks mobile targets in a 550 m × 400 m area at low power, making it a QoS-aware, modular service architecture that easily integrates into existing LBS systems. © 2008-2012 IEEE.