Improve Design Antenna by Using Machine Learning and Material
Abstract
This study presents improve a MIMO antenna system using machine learning, aiming for broad frequency coverage, high gain, compact size, and excellent isolation. The antenna employs four elements arranged orthogonally on a compact substrate, integrating a multi-slotted radiating patch and a partial ground plane. The absence of a meta surface is compensated by leveraging machine learning techniques to optimize the antenna's performance. Through regression methods, particularly linear regression, the antenna achieves remarkable accuracy in gain and efficiency validation. This approach underscores the crucial role of machine learning in refining antenna designs, enhancing their effectiveness in various applications such as Vehicle-to-Everything (V2X) communications within the 5G application.
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