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Physics

Artificial Intelligence Reshapes Microwave Photonics

Peng Li, Xihua Zou, Jia Ye, Wei Pan, Lianshan Yan

Featured June 12, 2026

Original Paper

AI-generated analysis — This is SciGrove's AI interpretation of the paper, not peer-reviewed content. Always refer to the original paper.

Simply

Smart computer programs are making microwave light systems much better by helping them learn from data, automatically fix problems, and work on their own, like a self-driving car for signals.

In depth
The paper reviews how artificial intelligence (AI) is transforming microwave photonics (MWP) by enabling data-driven modeling and autonomous operation across signal generation, transmission, and processing. This integration allows MWP systems to overcome traditional limitations like manual calibration and fixed architectures, leading to self-optimizing platforms capable of handling complex nonlinearities and dynamic environments.

Key Takeaways

  • 1
    AI is driving the evolution of MWP into an intelligent era (MWP 3.0), moving beyond bandwidth and miniaturization to autonomous, data-driven systems.
  • 2
    Machine learning and deep learning models enable real-time optimization and nonlinear distortion compensation across MWP signal generation, transmission, and processing.
  • 3
    AI-enabled MWP systems achieve superior accuracy, efficiency, and adaptability, leading to breakthroughs in areas like end-to-end link optimization and self-interference cancellation.

Conceptual Flow

HIGH LEVEL
1
AI Learns Complex Signal Behavior

Computers learn how light signals change as they travel, instead of needing exact math rules.

Raw Signal Data
Channel Effects
Find Hidden Rules
Smart Prediction Model
2
Smarter, Faster Signal Systems

This makes microwave light systems work better, faster, and without constant human help.

Old System
Slow Adjustments
AI Improves Everything
Fast, Self-Tuning System

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Artificial Intelligence Reshapes Microwave Photonics | SciGrove