Online DWDM Optical Link SNR Monitoring With Digital Correlation
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Solution Overview
Problem
Conventional optical performance monitoring techniques for in-service wavelength channels in DWDM optical links are computationally expensive, require additional hardware, and have limited capability to monitor signal-to-noise ratio (SNR).
Innovation Solution
A method and system for determining spectrum-resolved SNR in an online DWDM optical link by converting optical signals to digital, processing to extract noise-affected signals, reconstructing original signals, and correlating time-domain portions to calculate SNR, with optional averaging and segregation of transceiver and link noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optical performance monitoring techniques are used, then SNR monitoring capability is provided, but computational complexity increases and additional hardware is required
Solution Approach 1:
The system uses the received optical signal itself to generate the reference signal through digital processing (decoding and reconstruction), eliminating the need for separate reference signal generation hardware. The digital signal processor leverages the signal's own structure (encoded data) to create a clean reference version for comparison.
Solution Approach 2:
The patent replaces optical domain operations with digital signal processing operations. Instead of using optical splitters, filters, and separate reference paths, the system uses digital decoding, reconstruction, and correlation algorithms to achieve the same SNR measurement function with reduced hardware.
2Measurement precision
If spectrum resolution is implemented, then noise characterization accuracy improves, but processing complexity increases
Solution Approach 1:
The frequency spectrum is divided into multiple discrete frequency bins through FFT processing. Each bin represents a specific frequency component where SNR can be independently calculated, enabling detailed noise characterization across the spectrum while using standard digital signal processing techniques.
Solution Approach 2:
The patent transforms the time-domain signals into the frequency domain using Fast Fourier Transform (FFT). This dimensionality change from time to frequency domain enables spectrum-resolved SNR calculation by analyzing signal and noise power at different frequency components separately.
3Productivity
If online monitoring is implemented for in-service channels, then system operational efficiency improves, but measurement accuracy may be compromised
Solution Approach 1:
The system performs decoding and signal reconstruction before the correlation measurement step. By preparing a clean reference signal in advance through digital processing of the received signal, the system ensures accurate SNR measurement can be performed on the actual received signal without requiring signal interruption or additional hardware.
Solution Approach 2:
The system uses the decoded and reconstructed signal as feedback to create a reference that accounts for the actual transmitted content. This reference signal is then correlated with the received signal to accurately measure SNR, ensuring the measurement reflects the true channel conditions while maintaining online operation.
Data Source
AI summary
The disclosed systems and methods for determining spectrum-resolved signal-to-noise ratio (SNR) in an online dense wavelength division multiplexing (DWDM) optical link, the method comprising: i) receiving a noise affected optical signal; ii) converting the received optical signal into a digital signal; iii) processing the digital signal to extract the noise affected transmitted signal; iv) decoding the noise-affected transmitted signal and reconstructing an original transmitted signal; v) converting the noise-affected transmitted signal into frequency domain noise-affected transmitted signal; vi) converting the original transmitted signal into frequency domain original transmitted signal; vii) selecting spectrum slices from the frequency domain noise-affected transmitted signal and the frequency domain original transmitted signal; viii) converting the spectrum slices into time domain portions of the noise-affected transmitted signal and the original transmitted signal respectively; ix) correlating the time domain portions of the noise-affected transmitted signal and the original transmitted signal; and x) determining the spectrum-resolved SNR.