Real-World LoRaWAN Performance and Propagation Modeling Using UAV, Helikite, and Vehicle-Based Measurements

2026-04-07

AI Summary

This study systematically investigates the impact of platform altitude, mobility, and terrain on LoRaWAN signal propagation performance. Empirical data were collected in urban and rural non-line-of-sight environments using ground vehicles, a 50-meter multirotor drone, and tethered helium balloons at 150 and 300 meters. Through analysis of RSSI and SNR, adaptive spreading factor strategies, and log-distance path loss modeling optimized via error minimization, the work reveals how signal strength and SNR vary with distance and spreading factor across platforms. It presents the first integrated evaluation of diverse aerial–terrestrial platforms for characterizing LoRaWAN propagation in complex real-world settings, demonstrating that the stable high-altitude balloon platform yields the most reliable links, whereas drones and ground vehicles suffer significantly from obstruction and multipath effects. The study also validates the effectiveness of adaptive spreading factor selection in enhancing communication reliability.

Abstract

This paper presents a field-based evaluation of Long Range Wide Area Network (LoRaWAN) signal propagation conducted at two locations within the Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) testbed: Lake Wheeler Field and NC State University's Centennial Campus. Three distinct transmission platforms were deployed, a ground vehicle, a multirotor drone at 50 meters, and a helikite at a steady altitude of 150 meters and 300 meters approximately. These platforms enabled a comparative study on how altitude, mobility, and terrain influence wireless signal reception across a LoRaWAN gateway network. We analyze received signal strength (RSSI) and signal-to-noise ratio (SNR) as functions of distance and spreading factor (SF). Three complementary metrics are visualized: SNR versus distance with demodulation thresholds, probability of successful reception, and SNR boxplots grouped by distance bins. These plots reveal link degradation patterns and demonstrate the role of adaptive SF selection in maintaining communication reliability. To characterize propagation behavior, we apply a log-distance path loss model to empirical data from the ground vehicle experiment, which encompass both rural and urban non-line-of-sight (NLOS) conditions. Model parameters are optimized through error minimization techniques. Our results show that the helikite platform, due to its stable high-altitude position, provided the most reliable and consistent link performance. Conversely, the drone and vehicle exhibited higher variability due to movement, obstructions, and terrain-induced multipath. These findings demonstrate the influence of platform dynamics and altitude on LoRaWAN reception performance, providing support for future aerial network planning efforts.

Problem

• LoRaWAN
• signal propagation
• UAV
• helikite
• path loss

Innovation

• LoRaWAN
• UAV
• helikite
• propagation modeling
• adaptive spreading factor