ANN-based design of miniaturized circular dual-band 4×4 MIMO antenna for 28/38 GHz 5G mmWave applications

Abstract

This paper introduces an innovative approach to design an extremely compact circular dual-band antenna suitable for 28/38 GHz 5G mmWave communications. Leveraging artificial neural network (ANN) and specially, multilayer perceptron (MLP) architecture, the suggested antenna’s dimensions, which allow it to resonate across both frequencies, are predicted. The proposed circular patch antenna, featuring strategically placed rectangular and circular slots in the patch and the ground plane, attains a remarkable frequency range of 3 and 2 GHz for the initial resonant frequency of 28 GHz and the subsequent resonant frequency of 38 GHz bands, respectively. With maximal gains of 4.5 and 7 dB at the corresponding resonance frequency, respectively, the antenna also exhibits high efficiency. Remarkably, the dimensions of the individual antenna element are compact, measuring 4×6×0.8 mm³, showcasing a notable decrease in physical footprint. Furthermore, the single antenna seamlessly transforms into a 4×4 multiple input multiple output (MIMO) antenna occupying a total volume of 16×16×0.8 mm³, showcasing superior isolation and good diversity performance. This research not only contributes significantly to advancing miniaturized dual-band antennas tailored for 5G mmWave applications but also underscores the effectiveness of ANN, particularly MLP architecture, in optimizing antenna designs. The proposed antenna, with its small form factor, stands out as a promising solution for new generation 5G communication systems.