Machine Learning-enabled method for Design, Modelling and optimization of Microwave Antennas and RF Devices
Santosh Gore
Abstract
Microwave antennas and radiofrequency (RF) devices are crucial elements in modern communication systems such as wireless communications, radar, and satellite communication. Designing, modeling, and optimizing these components can be challenging due to their complex geometries and electromagnetic properties. However, the use of machine learning (ML) has provided significant improvements in microwave engineering by enhancing the efficiency and performance of these components. This article presents a comprehensive review of recent developments in ML-enabled methods for the design, modeling, and optimization of microwave antennas and RF devices. The article discusses various ML techniques, including neural networks, support vector machines, and evolutionary algorithms, and their applications in antenna and device design. Furthermore, the article highlights the advantages and limitations of these methods and proposes future research directions in this field