EM Simulation, Implementation and Performance Evaluation of a Varactor-Based Reconfigurable Intelligent Surface

Reconfigurable Intelligent Surfaces (RIS) are passive antenna arrays capable of dynamically modifying their reflective properties to adapt to variations in the communication channel by adjusting the reflection coefficient of each unit cell. RIS technology has attracted significant attention for its potential to enhance wireless communication systems, with envisioned applications in smart cities, indoor environments, and 5G/6G networks, enabling more reliable and adaptive communications. This paper presents the design, simulation, implementation, and validation of an RIS operating at 9.6 GHz, composed of a 40× 40 array of unit cells, where reconfiguration is achieved using Barium Strontium Titanate (BST) varactors in combination with a clustering strategy that groups five unit cells under a single control element. This approach reduces the number of independent finite elements and control lines by 80%, with a quantified worst-case performance loss of 1.72 dB. As a first step, material properties and physical phenomena such as mutual coupling between adjacent unit cells and surface edge effects were investigated through full-wave simulations. Additionally, the S-parameters of the varactor models were incorporated into the simulations to apply programmable phase shifts across the surface, while statistical variations due to component tolerances were also considered to model realistic performance degradation. The designed surface was subsequently fabricated and experimentally validated, demonstrating strong correlation between measured and simulated results. A comparison between the deactivated and activated states of the RIS shows a reflection gain improvement exceeding 20 dB across the angular range from 20∘ to 80∘. Finally, the proposed RIS was thoroughly evaluated through both electromagnetic simulations and comparisons with idealized theoretical models, offering valuable insights into practical performance degradation and reinforcing the importance of comprehensive performance evaluations under real-world hardware constraints.