Ultra-Wideband CPW Fed Band-Notched Monopole Antenna Optimization Using Machine Learning

Abstract

In this article, a compact Coplanar Waveguide (CPW) fed band-notched monopole antenna is designed and optimized. The unique feature of this article is to provide an approach for designing an antenna in the best way using machine learning techniques. Machine Learning can be used to speed up the antenna design process. There are five algorithms employed: Decision Tree, Random Forest, XGBoost Regression, K-Nearest Neighbor (KNN), and Artificial Neural Network (ANN). Among all the algorithms, KNN gives the best result with accuracy up to 98%. From the obtained result, we can estimate the dimensions of the desired parameters, which could not be done previously by High Frequency Structure Simulator (HFSS) Electromagnetic (EM) simulator. The optimized antenna design is also fabricated and tested, which confirms its frequency range between 2.9 and 21.6 GHz. Stable radiation features in between the operating frequency range makes it suitable for Ultra-Wideband (UWB) applications.

Circularly polarized printed dual port MIMO antenna with polarization diversity optimized by machine learning approach for 5G NR n77/n78 frequency band applications

“…Ranjan et al built five machine-learning models to propose a UWB-compatible CPW-fed monopole radiator. Predictions match simulations and measurements 34 .…”

Effective modeling of metasurface‐loaded circularly polarized dielectric resonator‐based MIMO antenna for sub‐6.0‐GHz band using machine learning algorithms

“…8 Recently, Ranjan et al used the ANN and random forest-based ML algorithms to optimize the ultra-wideband monopole printed antenna. 9 In this article, various ML algorithms are utilized to optimize the dual-port circularly polarized dielectric resonator antenna with circular polarization features. Three different ML algorithms are utilized to predict the reflection coefficient and mutual coupling of designed antenna.…”

“…Singh et al used the different ML algorithms to predict the |S 11 | outcome of microstrip line coupled DRA 8 . Recently, Ranjan et al used the ANN and random forest‐based ML algorithms to optimize the ultra‐wideband monopole printed antenna 9 …”

A Design of Dual-Band Coplanar Waveguide (CPW) Printed Antenna for 1.9-3.6GHz Applications

“…This type of waveguide has an additional third conductor centered in the slot region and specifically useful in developing active circuitry. The presence of the additional strip can support even or odd quasi-TEM mode at low frequencies as well as TE mode at high frequencies [3]. The modification of the dimensions of the signal strip or ground plane such as thickness, length and width play a vital role in determining the characteristics of a CPW-fed antenna [2].…”