A Sparse Reconfigurable Intelligence Metasurface
Mengyao Zhao, Xinyu Cai, Zhangjie Luo · 2024
While the reconfigurable intelligence metasurface (RIS) has attracted tremendous attention in recent years, it suffers from high cost and power consumption due to the use of a large number of electrically tunable components. Here, we propose a 2-bit sparse RIS for beam-scanning application in the X-band. It is composed of 196 digitally encoded unit cells; but different from conventional RIS, the number of tunable unit cells is largely reduced by 33.7%, and it can still maintain the beam-scanning range from -60° to 60° in the E-plane with the sidelobe below -12 dB. This is realized by a delicate sparse design that is optimized using a dual-layer nested genetic algorithm, which is presented in the paper.