A stochastic wideband propagation-graph channel model for plants-affected drones air-to-ground mmWave communications

Abstract

Unmanned aerial vehicles (UAVs) are experiencing extensive worldwide application across various fields, particularly in outdoor scenarios that often involve vegetation. A comprehensive understanding of the air-to-ground (A2G) wireless link channel and fading characteristics is crucial for the deployment and optimization of communication systems. In this paper, we propose a A2G wideband wireless channel model that integrates line-of-sight (LoS), reflection, and scattering propagation mechanisms at typical millimeter-wave (mmWave) bands based on the stochastic propagation-graph model. First, a geometric fractal tree modeling method is introduced to represent a single tree, the size and distribution of trees are modeled based on the stochastic theory. The propagation-graph (PG) model is then employed to simulate the A2G channel impulse response (CIR) at 28 GHz, taking into account maximal propagation delay constraints. On this basis, we investigate the spatial cross-correlation function (CCF) at different positions and effects of different UAV heights and circular movement radii on delay spread. Additionally, we study key small-scale statistical channel properties, including the power delay profile (PDP), power angular profile (PAP), and Doppler power spectrum density (DPSD). Our simulation results demonstrate that vegetation significantly impacts channel dispersion in spatial-temporal-frequency domains, and our model effectively captures the non-stationarity of UAV A2G channels.