Antenna Optimization using Machine Learning Algorithms and their Applications: A Review
Anil Pandey, M. P. Singh
Abstract
Antenna optimization using machine learning is a rapidly evolving field that leverages the power of artificial intelligence to design and improve antenna systems.Antenna optimization is a process of modifying antenna parameters to achieve desired performance metrics, such as gain, bandwidth, radiation pattern, and impedance matching.This paper presents a review of the most advanced development in antenna design and optimization by using machine learning techniques.The aim of this survey is to focus on different machine learning optimization techniques and their optimization capability with efficiency challenges.A deep outline from literature survey on optimization of antennas using machine learning are presented and listing various optimization algorithms and procedures that are applied to produce desired antenna characteristics and specifications.Firstly, a brief introduction of machine learning and its algorithms, later a quick explanation of antenna optimization process followed by an arranged introduction of different types of printed antenna designs using machine learning algorithm are reported.The methods emphasized in this survey have probably an effect on the imminent advancement of antennas for a variety of wireless applications.