A Building Height-Dependent Gaussian Mixture Model to Characterize Air-to-Ground Wireless Channels

With the continuous evolution of Unmanned Aerial Vehicles (UAVs) in terms of flight autonomy and high payload capabilities, many new applications have emerged recently. In this context, potential usage of UAVs has been explored in providing wireless communication service. However, our understanding of the wireless channels associated with UAVs is still in its infancy. Therefore, in this paper, we use ray-tracing simulations to develop a novel Gaussian Mixture Model (GMM) for Air-to-Ground (A2G) channels. An urban environment with mean building heights of 10 m, 20 m, 50 m, and 80m is considered to develop the proposed model. An extensive set of simulations are performed using a raytracing simulator, Wireless InSite (R). Our results show that the Probability Density Function (PDF) of the received power or the path loss vary depending on the mean building height and can be modelled using a GMM. The proposed model is then validated by using it to generate PDFs of a certain test set of city environments.