ABSTRACT

In this paper, an 8-bit programmable digital metasurface is designed in the operating frequency range from 4 to 7 GHz. A monopole antenna operating at 5 GHz is characterised by using a metasurface structure as the ground plane. Various combinations of the metasurface structure are examined by altering the state of each unit-cell between ‘ON (1)’ and ‘OFF (0)’ in the coding matrix. The purpose of the 8-bit programmable digital metasurface is to control the electromagnetic wave effectively in the frequency range of interest. Dynamically controllable metasurface structure is utilised to change the unit cells’ configurations. In addition, the proposed adjustable metasurface is capable to control the monopole antenna directivity, gain and main lobe magnitude, efficiently. According to various via conditions, different metasurface-based antenna parameters such as return loss (S₁₁), radiation pattern, directivity and surface current distribution are investigated by means of the commercial numerical simulation software, CST microwave studio. Employing the simulation results of the metasurface-based antennas, the artificial neural network (ANN) data set is obtained. 128 activation conditions are trained and tested by Levenberg Marquart learning algorithm. During the ANN procedure, MATLAB is used to obtain accurate results by changing the rate of test and training data set.

摘要

本文设计了一种工作频率为4~7 GHz的8位可编程数字超表面。工作频率为 5 GHz 的单极天线的特点是使用超表面结构作为接地平面。通过改变编码矩阵中“ON (1)”和“OFF (0)”之间每个单位单元的状态来检查超表面结构的各种组合。8位可编程数字超表面的目的是在感兴趣的频率范围内有效地控制电磁波。利用动态可控的超表面结构来改变单元电池的配置。此外，所提出的可调节超表面能够有效地控制单极天线的方向性、增益和主瓣幅度。根据各种过孔条件，_{如图11所示}），利用商用数值模拟软件CST微波工作室研究了辐射方向图、方向性和表面电流分布。利用超表面天线的仿真结果，获得人工神经网络（ANN）数据集。128个激活条件通过Levenberg Marquart学习算法进行训练和测试。在 ANN 过程中，MATLAB 用于通过改变测试和训练数据集的速率来获得准确的结果。