Adaptive Filter Tap Windowing for Low-SNR Waveguide Estimation
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Solution Overview
Problem
Existing digital coherent communication systems face challenges in accurately estimating differential group delay and polarization dependent loss when the signal-to-noise ratio of optical signals is below a predetermined value, leading to decreased estimation accuracy.
Innovation Solution
A waveguide estimation device and method that employs time window processing and threshold-based filtering of tap coefficients in a digital coherent receiver to improve the estimation accuracy of differential group delay and polarization dependent loss by selectively using tap coefficients within a time window and applying a time or frequency window function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of taps of the adaptive filter is increased to compensate for large waveform distortion, then the compensation capability is improved, but the operation amount and power consumption of digital signal processing increase
Solution Approach 1:
The patent extracts and processes only the significant tap coefficients by applying a time window function that concentrates energy around the peak tap. This selective processing approach allows the system to achieve effective distortion compensation using only a subset of the total taps, thereby reducing the operation amount and power consumption while maintaining compensation capability.
Solution Approach 2:
The patent segments the tap coefficients into significant and insignificant portions based on their magnitude relative to the peak tap. By applying the time window function only to taps within a certain range of the peak (where the window function value exceeds a threshold), the system divides the processing workload into essential and non-essential parts, reducing overall computational burden.
2Reliability
If the number of taps of the adaptive filter is increased to handle large waveform distortion, then the compensation capability is improved, but the device complexity increases
Solution Approach 1:
The patent extracts only the significant tap coefficients that contribute meaningfully to distortion compensation. By identifying the peak tap and processing only taps within a certain distance from the peak (where the time window function exceeds a threshold), the system reduces the effective number of coefficients that need to be stored and processed, thereby reducing device complexity.
Solution Approach 2:
The patent introduces a dynamic thresholding mechanism where the significance of each tap coefficient is determined by its distance from the peak tap and the value of the time window function. This dynamic approach allows the system to adaptively determine which taps are significant, reducing the fixed complexity of the filter while maintaining compensation capability for varying distortion levels.
3Measurement precision
If standard estimation methods are used for differential group delay and polarization dependent loss, then the estimation process is simple, but the estimation accuracy decreases when signal-to-noise ratio is below a predetermined value
Solution Approach 1:
The patent converts the harmful effect of noise on estimation accuracy into a benefit by using the time window function to suppress noise in the tap coefficients before estimation. The window function concentrates the signal energy around the peak while attenuating noise components, thereby improving the signal-to-noise ratio for the estimation process and enabling accurate estimation even in low SNR conditions.
Solution Approach 2:
The patent applies preliminary processing to the tap coefficients by multiplying them with the time window function before performing the estimation of differential group delay and polarization dependent loss. This preliminary action of windowing prepares the data by reducing noise and emphasizing significant components, thereby improving subsequent estimation accuracy without requiring changes to the estimation algorithms themselves.
Data Source
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AI summary
A waveguide estimation device includes: a time window processing unit that multiplies time-series tap coefficients of an adaptive filter by a time window function; and an estimation unit that estimates at least one of a differential group delay in a frequency series or a time series and a polarization dependent loss in a frequency series or a time series based on the time-series tap coefficients in a time window. The estimation unit may estimate at least one of the differential group delay in a frequency series or a time series and the polarization dependent loss in a frequency series or a time series based on a tap coefficient exceeding a lower limit threshold value or falling below an upper limit threshold value among the time-series tap coefficients in a time window. The estimation unit may estimate the average value of the differential group delays in a frequency series or a time series. The time window processing unit may determine the length of the time window based on a constant multiple of the average value.