Enhancing Antenna Design through machine learning and Explainable AI For Optimal Performance

Antenna design plays a crucial role in modern wireless communication systems, influencing signal quality, coverage, and performance.Traditional approaches to antenna design depend on empirical methods and optimization through simulation, processes that can be both time-consuming and require significant resources.Recent progress in deep learning and explainable artificial intelligence (XAI) presents novel methods to improve antenna design procedures.This paper examines the use of deep learning models to enhance antenna performance and discusses the integration of XAI methods to offer clarity and understanding of these models.We explore different deep learning models, their use in antenna design, and approaches for understanding model predictions.A case study shows how effective these methods are in the design of a microstrip patch antenna.Our results suggest that combining deep learning with XAI methods can greatly enhance the efficiency and effectiveness of antenna design.