Abstract:
This paper presents a deep learning approach for the design of on-demand reconfigurable reflectarray elements. By leveraging microwave network analysis, our technique eff...Show MoreMetadata
Abstract:
This paper presents a deep learning approach for the design of on-demand reconfigurable reflectarray elements. By leveraging microwave network analysis, our technique efficiently reduces the dataset size by half. We introduce a novel target function to obtain high-performance elements. The benefits of this approach are experimentally demonstrated by automatically generating an on-demand wideband 1-bit reconfigurable reflectarray element, significantly enhancing the bandwidth performance compared to conventional designs.
Published in: 2024 IEEE International Symposium on Antennas and Propagation and INC/USNC‐URSI Radio Science Meeting (AP-S/INC-USNC-URSI)
Date of Conference: 14-19 July 2024
Date Added to IEEE Xplore: 30 September 2024
ISBN Information: