An angle of arrival estimation method for intelligent metasurface using machine learning

Abstract

Today, techniques for altering electromagnetic waves and the data they transport are increasingly crucial. These techniques have become increasingly important in several communication technologies, such as intelligent metasurface, with the rise and development of next-generation wireless communication systems. Since those technologies call for locating devices, angle of arrival (AoA) analysis becomes a crucial area for research. The AoA can now be shown in various ways, and some subspace methods have already achieved great precision. However, the extensive calculation required by those techniques is one of their key shortcomings. The author developed a novel radio frequency (RF) switching circuit design in this research and applied a novel machine-learning method to signal AoA. In single-wave settings, it was discovered that the proposed machine learning method performed satisfactorily with an average difference of 0.6 degrees.