Optimizing the design of intelligent reflecting surfaces with graphene for maximum wireless power transfer in Internet of Things communications

Abstract To meet the growing demand for higher data speeds and denser network coverage, intelligent reflecting surfaces (IRS) have gained considerable attention owing to their ability to control electromagnetic waves with accurate beam orientation. However, an optimal IRS design for maximum wireless power transfer (WPT) is essential and requires the integration of tuning features into reflect arrays. Earlier studies employed varactor and PIN diodes for the tuning of metallic reflectors; by contrast, graphene offers inherent tuning without extra components owing to its unique material properties. We propose the design of optimal graphene‐enabled IRS (GIRS) to maximize WPT in Internet of Things (IoT) communications. Specifically, we formulate an optimization problem to maximize the power received by an IoT user, thereby obtaining a global optimal solution in terms of the Fermi level of GIRS. Furthermore, the closed‐form expression of the Fermi level was derived as a function of the reflection amplitude controlled by GIRS, incident frequency, and other GIRS parameters. Finally, we numerically validated all investigations and provide several insights into the necessary GIRS design parameters.