Three-Dimensional Geometry-Based Stochastic Channel Modeling for Intelligent Reflecting Surface-Assisted UAV MIMO Communications

Abstract

In this letter, a three-dimensional (3D) geometry-based stochastic multiple-input multiple-output (MIMO) channel model for intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) communications is proposed. The IRS is distributed on the surface of buildings to assist the UAV transmitter to reflect its signals to the receiver on the ground level and to improve the communication quality by passive beamforming at the IRS. In such a channel model, the signals transmitted from the UAV transmitter will first get scattered by the clusters between the UAV and IRS before arriving at the IRS, and subsequently arrive at the ground receiver. We separate this channel model into a subchannel model between the UAV and the IRS, as well as a subchannel model between the IRS and the receiver. Based on the derivations of complex channel coefficients for the above two subchannel models, we investigate the impact of IRS on the underlying propagation channel by studying the spatial cross-correlation functions (CCFs). Simulation results are provided to show the statistical propagation characteristics of the IRS-assisted UAV MIMO channels.