Deep Learning-Aided Predictive Model for Precision Design and Rapid Prototyping of Metamaterial-based 5G Antennas for Biomedical Applications

The advent of 5G technology has revolutionized wireless communication, bringing unprecedented speed and connectivity. However, it also presents new challenges, particularly in antenna design, where performance, size, and health-related concerns are paramount. This research explores the use of deep learning models to predict key antenna characteristics, such as the S11 parameter and gain, based on antenna dimensions. By leveraging an open-source dataset on metamaterial antennas, the study delves into the potential of metamaterials to enhance 5G communication systems, especially in applications like wearable devices, smart devices and healthcare monitoring devices. Meta-materials, with their unique properties, offer promising solutions to the inherent challenges of 5G, such as low coverage and high environmental absorption. This paper also discusses how AI can streamline the traditionally time-consuming process of antenna design, making it more efficient and accessible.