A Smart Metasurface for Electromagnetic Manipulation Based on Speech Recognition
Lin Bai,
Yuan Ke Liu,
Liang Xu,
Zheng Zhang,
Qiang Wang,
Wei Xiang Jiang,
Cheng-Wei Qiu,
Tie Jun Cui
Affiliations
Lin Bai
State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Yuan Ke Liu
State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Liang Xu
State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Zheng Zhang
State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Qiang Wang
State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Wei Xiang Jiang
State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China; Purple Mountain Laboratories, Nanjing 211111, China; Corresponding authors.
Cheng-Wei Qiu
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore; Corresponding authors.
Tie Jun Cui
State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China; Corresponding authors.
In this work, we propose and realize a smart metasurface for programming electromagnetic (EM) manipulations based on human speech recognition. The smart metasurface platform is composed of a digital coding metasurface, a speech-recognition module, a single-chip computer, and a digital-to-analog converter (DAC) circuit, and can control EM waves according to pre-stored voice commands in a smart way. The constructed digital metasurface contains 6 × 6 super unit cells, each of which consists of 4 × 4 active elements with embedded varactor diodes. Together with the DAC and single-chip computer, the speech-recognition module can recognize voice commands and generate corresponding voltage sequences to control the metasurface. In addition, a genetic algorithm (GA) is adopted in the design of the metasurface for efficiently optimizing the phase distributions. To verify the performance of the smart metasurface platform, three typical functions are demonstrated: radar cross-section reduction, vortex beam generation, and beam splitting. The proposed strategy may offer a new avenue for controlling EM waves and establishing a link between EM and acoustic communications.
