Empirical Dynamic Modeling for Low-Altitude UAV Propagation Channels

During the last few years, with decrease of their sizes and costs, Unmanned Aerial Vehicles (UAVs) became more feasible for use in general-purpose applications. As an important basis UAV applications, Air-to-Ground (A2G) radio propagation channel has gained attention modeling literature. However, whereas A2G is inherently dynamic (time-varying), majority available models do not consider such a time-variability. This paper proposes multi-path component (MPC) tracking algorithm shows its ability to analyze data collected by real measurement campaign suburban environment. Based on obtained results, time-varying statistical model communications realistic scenarios proposed. The able stochastically characterize parameters related birth time-of-life components (MPCs), as well evolution terms delay, Doppler frequency or magnitude. Correlation coefficients relate different characteristics are also obtained. Our work that MPCs over time can be described simple regular patterns.