Learning from UAV Experimental Results for Performance Modeling of Reconfigurable Intelligent Surface Flying Platform

In this paper, we obtain data from unmanned aerial vehicle (UAV) hovering experiment which contains jittering effect. Not only do we discover the essence of the jittering by analyzing the statistical property of the data, but we model it as well. To simplify the experimental procedure and avoid repeatedly doing experiments, we come out with the algorithm based on what we model, to generate data. UAV, as a flying vehicle, has the advantage of being highly mobile, being able to build line-of-sight (LoS) connection, and effectively promoting the throughput of wireless communication network. Reconfigurable intelligent surface (RIS) is a passive antenna array that has multiple advantages, such as being able to shape the communication environment by reflecting incident signal, energy saving and environmental friendly. In our application scenario, we let UAV carry RIS to support wireless communication network and consider the effect of jittering. It turns out that the data generated by algorithm and which generated by experiment have a similar impact on the average achievable rate at the receiving end.