Revolutionizing Microwave Circuit Design with Machine Learning: Challenges and Opportunities

Abstract

The progress of wireless communication systems is highly dependent on microwave technologies. With the escalating adoption of higher frequency bands in communication systems and the exponential growth of transistor densities in line with Moore's Law, microwave circuit design complexity and costs are mounting significantly. Machine learning (ML) has recently arisen as a transformative tool for improving wireless communications through various means. This research reviews existing ML-aided microwave circuit behavior analysis techniques, assesses the performance through case studies, and elaborates on various design methods to streamline microwave circuit design. This article also highlights the challenges and potential solutions for improving the efficiency and cost-effectiveness of design processes. Future research needs to focus on developing advanced ML architectures and integrating them into existing design methodologies to revolutionize microwave design and accelerate the advancement of wireless communication systems.