Title: Design and optimisation of CPW antenna using machine learning algorithms

Authors: M. Ravi Kishore; K.C.B. Rao

Addresses: Department of Electronics and Communication Engineering, JNTUK, Kakinada, AP, India ' Department of Electronics and Communication Engineering, JNTUGV, Vizianagaram, AP, India

Abstract: In this paper, a novel design and optimisation method of coplanar waveguide-based antenna with two radiating arms surrounded by coplanar ground has been proposed. Optimisation of lengths and widths of the CPW antenna arms produce better impedance matching, better gain and multiband radiation characteristics. The optimisation of the proposed antenna is carried out with the help of familiar machine learning algorithms namely KNN, decision tree, linear regression and ridge regression. These optimisation algorithms are implemented using python programming and applied to obtain optimised dimensions on the basis of root mean square error (RMSE). The output parameters chosen for optimisation are gain and bandwidth of the antenna. The proposed antenna is simulated, optimised and analysed using high frequency structure simulator (HFSS) software. The high gain antenna can be operated for dual resonance frequencies 2.4 GHz and 5.8 GHz with optimum bandwidth with peak gain of 10 dB.

Keywords: coplanar waveguide antenna; optimisation; machine learning algorithms; KNN; decision tree; root mean square error; RMSE.

DOI: 10.1504/IJQET.2024.140150

International Journal of Quality Engineering and Technology, 2024 Vol.10 No.1, pp.99 - 118

Received: 25 Oct 2022
Accepted: 14 Feb 2024
Published online: 25 Jul 2024 *

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