Design and performance optimization of fiber optic adaptive filters

Area of Science:

• Photonics
• Optical Signal Processing
• Adaptive Filtering

Background:

• There is a demand for efficient fiber optic systems capable of delaying and storing wideband guided lightwave signals.
• Existing optical adaptive filters primarily focus on electronic signals, not lightwave signals.

Purpose of the Study:

• To design and analyze a novel fiber optic adaptive filter for real-time processing of guided lightwave signals.
• To minimize electronic components by utilizing optical computation for signal processing.

Main Methods:

• Implementation of a least-mean-square algorithm-based fiber optic adaptive filter.
• Analysis of adaptive filtering convergence characteristics considering filter parameters and hardware errors.
• Computer simulations to validate theoretical performance optimization.

Main Results:

• The designed fiber optic adaptive filters can learn and adapt to input signal characteristics in real time.
• Optical computation is employed to leverage advantages in processing speed, parallelism, and interconnection.
• Optimal selection of filter parameters can reduce optical round-off errors and noise, and increase learning speed.

Conclusions:

• The developed fiber optic adaptive filters offer a versatile solution for real-time processing of lightwave signals.
• The design minimizes electronic devices, maximizing the benefits of optical computation.
• Performance optimization through parameter selection is validated by computer simulations.