Measurement-based Characterization of Human Body Impact on Ultra-low UAV-to-Ground Channels

Abstract

At ultra-low altitudes, an unmanned aerial vehicle (UAV) can act as a personal base station, where it communicates only with one user, as in the case of a UAV-assisted soldier. User equipment (UE) can be inside the pocket of a user or near their chest while facing or facing-away from the UAV. In these scenarios, the wireless channel can experience different fading levels based on the UAV's hovering position, user orientation, location of the UE near the user's body, and carrier frequency of the transmitted signal. In this work, we provide measurement results and study how the human body affects the Air-to-Ground (AtG) channel characteristics under various use cases of holding a UE device. These channel characteristics include the average signal strength, shadowing, and Rician K-factor. We target three different ways in which the device is held by the user: Near-Chest Facing, In-pocket Facing, and Near-Chest Facing-away from the transmitting UAV. We perform this study at carrier frequencies of 900 MHz and 2.5 GHz and in Line-of-Sight (LOS) conditions. First, we conduct a set of baseline experiments to understand AtG channels in free space with no human involved. Second, we conduct AtG experiments with the user holding the device and show that the human body can induce either gains or losses compared to free space, depending on the user orientation with respect to the UAV. Third, we find that there are two distinct regions of operation, one in which the channel characteristics are mainly affected by the UAV and another that is dominated by the user's body. The obtained results help create more realistic 3D UAV-to-ground channel models and complement adaptive aerial drone deployment algorithms that target making intelligent decisions about trajectory and energy consumption when considering human body effects.