Journal of Artificial Intelligence and Data Science

2791-8335

Izmir Katip Celebi University

Artificial Intelligence

Yapay Zeka

Machine Learning Predictive Wi-Fi Antenna Design for Wireless Communication Technologies

https://orcid.org/0000-0002-9636-3919

Demırbas

Gokcen

IZMIR KATIP CELEBI UNIVERSITY, FACULTY OF ENGINEERING-ARCHITECTURE

12 26 2022

2 2 82 86 07 29 2022 10 26 2022

2021

Journal of Artificial Intelligence and Data Science

The use of the Internet has become indispensable with the developing technology. Providing access to the internet, which is the most important part of technology, has become one of the greatest needs. Antennas are the most important stage to access the Internet. Recently, development studies have increased considerably for antennas, which are the first step of wireless communication technology. In this study, a Wi-Fi antenna design with 2.4 GHz operating frequency that can be used in wireless communication technology has been realized. Microstrip antenna has been chosen to meet the necessary needs. While designing the antenna, CST Microwave Studio program has been used and numerical calculations have been made. After the antenna design has been made, machine learning support has been provided. The most effective lengths of the antenna have been determined and parametric analysis has been performed. The results of the selected algorithms have been observed. Based on these results, the algorithm that made the closest prediction has been determined. As a result of this study, an antenna design with a return loss value of 21 dB and a bandwidth value operating between 2.37 GHz - 2.42 GHz frequencies has been carried out. The designed antenna is acceptable according to IEEE 802.11 standards. Decision Tree gave the best prediction result according to machine learning algorithms.

Wi-Fi Antenna Design Machine Learning Microstrip Patch

TUBITAK

1919B012102519

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