Performance Analysis of Intelligent Reflecting Surface-Aided Decode-and-Forward UAV Communication Systems

In this article, we consider a scenario of a decode-and-forward (DaF) wireless system supporting the communication of an unmanned aerial vehicle (UAV) with a ground-control-station (GCS) through an intelligent reflecting surface (IRS). Particularly, the UAV moves according to the three-dimensional (3D) random way point model at low altitude in a complex urban environment. However, a stationary relay-station (RS) decodes and forwards the UAV’s signal over an IRS-aided virtual line-of-sight (LoS) link to a GCS. The highly dynamic and terrain-dependent UAV-to-RS channel follows the Beaulieu-Xie fading model. However, the RS-to-IRS and IRS-to-GCS links enjoy clear LoS; thus, follow the Rice fading model. We derive new closed-form expressions for the probability density functions (PDFs) and the cumulative distribution functions (CDFs). Then based on the derived statistical expressions, several performance metrics including outage probability, average bit error rate, and ergodic channel capacity are derived in closed-forms. Additionally, simple and accurate approximated expressions in the high signal-to-noise ratio regime are also provided. The analytical results are validated through some representative numerical examples and supported by Monte-Carlo simulation results.