Artificial Intelligence Reshapes Microwave Photonics

2026-05-20

AI Summary

This work proposes an AI-driven research framework for microwave photonics, addressing the limitations of conventional systems that rely heavily on human expertise and struggle with high-dimensional complexity and dynamic environments. By deeply integrating artificial intelligence techniques—particularly deep learning and reinforcement learning—with core microwave photonic functionalities such as photonic-assisted microwave generation, photonic analog-to-digital conversion, and optical wireless communication, the framework enables autonomous optimization and intelligent operation across the entire system lifecycle, from component design to deployment. This approach overcomes traditional performance bottlenecks and has successfully enabled breakthrough systems, including a 320 GHz-bandwidth photonic analog-to-digital converter, 616 Gbit/s optical wireless communication, and an all-optical microwave radar, significantly enhancing both system performance and autonomy.

Abstract

As a rapidly emerging interdisciplinary field that intrinsically integrates microwave and photonics, microwave photonics (MWP) provides disruptive solutions to overcome the fundamental bandwidth of conventional electronic systems. By exploiting the inherently ultra-wide bandwidth and low-loss characteristics of photonic technologies, MWP enables the generation, transmission, processing, and detection of microwave, millimeter-wave, and terahertz signals. Representative breakthroughs include fully photonic microwave radar systems, photonic analog-to-digital converters with bandwidth up to 320 GHz, and photonic wireless communication systems achieving data rate as high as 616 Gbit/s. Meanwhile, the rapid growth of artificial intelligence (AI) is reshaping scientific research, engineering, and daily life in unprecedented ways, such as AI for science/engineering and AI co-scientist/assistant. Correspondingly, AI is profoundly reshaping MWP in all aspects, ranging from signal generation, transmission to signal processing and detection. AI has revolutionized the design, simulation, fabrication, testing, deployment, and maintenance of MWP systems, delivering autonomous operation and exceptional efficiency beyond traditional systems. Motivated by these developments, this Review Paper provides the first comprehensive overview of AI-enabled MWP, systematically summarizing the state-of-the-art advances and presenting insights for both the academic community and the broader public.

Problem

• Artificial Intelligence
• Microwave Photonics
• Signal Processing
• Bandwidth Limitation
• Intelligent Systems

Innovation

• Artificial Intelligence
• Microwave Photonics
• Autonomous Systems
• Photonic Signal Processing
• AI-enabled Design