Machine Learning Aided Design of Sub-Array MIMO Antennas for CubeSats Based on 3D Printed Metallic Ridge Gap Waveguides

In this paper, a machine learning-assisted approach is presented for the design of a 3D Printed Metallic Ridge Gap Waveguide-Based array MIMO antenna for inter-cube satellite (CubeSat) communication. The designed antenna has a total dimension of 15.5x10.5x5.78 mm(3) and is based on aluminum alloy powder (AlSi10Mg) with a conductivity of 2.04x10(7) S/m. The antenna exhibits wideband operation in V-band (59.3-66.6 GHz) with a stable realized gain of 10.5 dBi and radiation efficiency of 90% over the operating frequency.