Optical Link Performance Prediction Using Segmented OSNR Analysis
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Solution Overview
Problem
Existing optical transport networks face challenges in efficiently rerouting traffic due to link failures, as predicting optical link performance and spectral efficiency along reroute links is complex, particularly due to fiber nonlinearities and the dependency on terminal equipment performance.
Innovation Solution
A system and method that analyze optical transport networks by computing the effective optical signal-to-noise ratio (OSNR) for each optical link element, reducing computational resources and eliminating the need for additional hardware, using a processor to execute modules for linear and nonlinear OSNR calculations, and interpolating amplifier and fiber characteristics to determine optimal link performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to predict optical link performance and spectral efficiency, then accuracy is maintained, but computational time and resource requirements increase significantly
Solution Approach 1:
The patent segments the optical link into multiple optical link elements (OLEs), each representing a specific span of optical fiber between amplifiers. This segmentation allows the system to compute performance metrics for each element individually and combine them, reducing the overall computational complexity while maintaining prediction accuracy across the entire optical link.
Solution Approach 2:
The patent changes the computational parameters by pre-calculating and storing key characteristics (such as amplifier gains, noise figures, and fiber properties) in lookup tables. During runtime, the system retrieves these pre-computed parameters rather than recalculating them, significantly reducing computational time while preserving the accuracy of performance predictions.
2Measurement precision
If detailed nonlinear OSNR calculations are performed for each optical link element, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent divides the optical link into discrete optical link elements and applies segmented calculation methods for nonlinear OSNR. Each element's nonlinear effects are computed independently using simplified models, and the results are aggregated. This approach maintains accuracy by considering nonlinear effects at each segment while reducing overall computational complexity through modular processing.
Solution Approach 2:
The patent transforms complex nonlinear OSNR calculations into simplified parameter-based computations by pre-characterizing nonlinear effects as lookup tables containing pre-computed penalty values. The system retrieves and applies these parameters based on operating conditions rather than performing full nonlinear simulations, reducing computational complexity while preserving prediction accuracy.
3Measurement precision
If comprehensive analysis of amplifier and fiber characteristics is performed, then link performance prediction accuracy improves, but hardware requirements and computational resources increase
Solution Approach 1:
The patent creates simplified computational models (copies) of the physical amplifier and fiber characteristics through pre-computed lookup tables. These tables contain essential performance parameters derived from detailed physical characterizations, allowing the system to use lightweight computational representations instead of complex physical models, thereby reducing hardware requirements while maintaining prediction accuracy.
Solution Approach 2:
The patent transforms detailed physical characteristics of amplifiers and fibers into simplified operational parameters stored in lookup tables. By changing from continuous physical models to discrete parameter sets, the system reduces computational resource requirements and hardware complexity while preserving the essential behavior needed for accurate link performance prediction.
Data Source
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AI summary
A system for analyzing an optical transport network is provided. The system can generate a linear OSNR and an output power profile for each optical link element of an optical link based on an input power profile, amplifier characteristics, transport fiber characteristics, and a set of operating parameters. The system can generate a nonlinear OSNR for each optical link element based on the input power profile and transport fiber characteristics of each optical link element. The system can determine an expected performance metric for the optical link based on the linear OSNR, the non-linear OSNR, and a transmitter output OSNR. The system can designate the optical link as valid for use in the optical transport network if the expected performance metric is greater than or equal to a performance metric threshold.