A Novel Two-Stage Optimization Framework for Designing Active Metasurfaces Based on Multiport Microwave Network Theory
Jun Wei Zhang, Zhen Zhang, Jianan Zhang, Jun Wu, Jun Yan Dai, Qiang Cheng, Qingsha S. Cheng, Tie Jun Cui
Abstract
Reconfigurable and programmable metasurfaces have shown promising potential in a variety of fields because of their remarkable ability to control electromagnetic (EM) waves. However, the design of metasurface elements requires extensive high-cost EM simulations to obtain certain functionalities, limiting the metasurface developments and applications. In this work, we propose a novel two-stage optimization framework to design active metasurface elements based on microwave network theory and optimization methods. In the proposed framework, a low-cost multiport network model is first established to achieve the rapid prediction of the EM responses of the meta-elements containing multiple loads. Based on the low-cost multiport network model, a genetic algorithm (GA) is then used to choose suitable port loadings, such as tunable components, short-circuit, and open-circuit. For the tunable components, we adopt a gradient-based optimization method to determine their working states. To verify the performance of the proposed method, a reflection phase-modulated metasurface is designed and fabricated. Simulation and experimental results are in good agreement with design goals, demonstrating the effectiveness and efficiency of the proposed method.