Channel Measurements and Modeling in Drone-to-Ground Communications

The drones, which are expected to take part in next-generation communication systems, are used in many fields such as military, commercial and disaster management. The demand for drone use has been increasing day by day due to their flexible design and easy installation that is customized for various applications. Accurate modeling of drone channels is essential for creating, development, and optimization of the drone-to-ground communication systems. In this study, the statistical properties of drone-to-ground channels are investigated via the measurements based on the received signal strength indicator (RSS/RSSI) provided by the IEEE 802.11n Wi-Fi network standard. Using the measurements, the path loss exponent of the drone-ground channels is estimated. In addition, Rician, Nakagami-m and Log-normal distributions are adapted to the measurements obtained for different heights of the drone with the help of the maximum likelihood decision rule and the performance of these probability distributions in modeling the measured drone-ground channel statistics are compared with each other.