Nonlinear Penalty Estimation via Spectral Inversion in Optical Networks

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Solution Overview

Problem

Optical transport networks face challenges in efficiently compensating for nonlinear impairments, particularly nonlinear phase noise, due to the computational intensity of digital signal processing and the impracticality of symmetric spectral inverter placement in real-world systems.

Innovation Solution

A method and system for estimating nonlinear noise in optical transport networks by calculating nonlinear transfer function integrals before and after spectral inversion nodes, allowing for optimal placement of spectral inversion nodes based on minimum noise values, thereby reducing computational resources and enabling asymmetric implementations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If digital signal processing is used to compensate for nonlinear phase noise, then compensation effectiveness is improved, but computational resource consumption increases

Engineering Contradiction:
Improvenonlinear phase noise compensation effectivenessVSAvoidcomputational resource consumption
Core Design Contradiction:
ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent pre-calculates and stores nonlinear transfer function integral values for each link in the optical path before actual signal transmission. These pre-computed values are then retrieved and used during operation, avoiding the need for real-time computation of nonlinear penalties and reducing online computational resource consumption while maintaining compensation effectiveness

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent divides the optical transmission path into multiple discrete links between nodes. The nonlinear transfer function integrals are calculated and stored for each individual link separately. This segmentation allows the system to retrieve and combine only the necessary link-specific values for a given path, rather than computing the entire path's nonlinear penalties from scratch, thus reducing computational resources

Inventive Principle:
Principle #1Segmentation

2Reliability

If spectral inverters are placed at the central location for optimal compensation, then nonlinear phase noise mitigation is improved, but system flexibility and practical deployment are reduced

Engineering Contradiction:
Improvenonlinear phase noise mitigationVSAvoidspectral inverter placement flexibility
Core Design Contradiction:
ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent removes the requirement for symmetric placement of spectral inverters at the central location. By pre-calculating nonlinear transfer function integrals for each link, the system can evaluate and optimize spectral inverter placement at any node position along the optical path. This allows asymmetric placements that adapt to practical network constraints while maintaining or improving nonlinear phase noise mitigation through optimized positioning based on pre-computed integral values

Inventive Principle:
Principle #4Asymmetry

3Measurement precision

If extensive computational resources are allocated for real-time nonlinear penalty calculation, then compensation accuracy is improved, but system cost and complexity increase

Engineering Contradiction:
Improvenonlinear penalty calculation accuracyVSAvoidsystem computational complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent performs the computationally intensive calculation of nonlinear transfer function integrals in advance, before actual signal transmission and penalty evaluation. These pre-computed values are stored for quick retrieval during operation. This preliminary computation maintains high accuracy in nonlinear penalty calculation while dramatically reducing the real-time computational resources and system complexity required during actual deployment

Inventive Principle:
Principle #10Preliminary action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach allows for efficient calculation and evaluation of nonlinear penalties, improving network performance and utilization by decreasing computational resources, thus enabling more flexible and economically feasible spectral inversion placements.

Implementation Method 1

Mid-span spectral inversion may be achieved optically (using optical phase conjugation based on an optical parametric process) or electronically (using an optical-electrical-optical (OEO) conversion). Accordingly, spectral inverters may change or maintain the wavelength after performing spectral inversion.

Methodology Applied
Scientific EffectSpectral inversion:

Implementation Method 2

Mid-span spectral inversion may be achieved optically (using optical phase conjugation based on an optical parametric process)

Methodology Applied
Scientific EffectOptical phase conjugation:

Implementation Method 3

The accumulated CD and NLPN of an optical signal may become reversed after spectral inversion is performed. Thus, to have optimal compensation of CD and NLPN, placement of spectral inverters has typically been limited to a central location (the mid-point) of a transmission link

Methodology Applied
Scientific EffectChromatic dispersion compensation:

Data Source

PatentUS9912435B2Nonlinear penalty estimation using spectral inversion in optical transport networks
Publication Date: 2018.03.06 1FINITY INC
  • US9912435B2 patent drawing
  • US9912435B2 patent drawing
  • US9912435B2 patent drawing

AI summary

Methods and systems may estimate nonlinear penalties for optical paths using spectral inversion in optical transport networks. Certain values of nonlinear transfer functions for nonlinear penalty estimation may be pre-calculated for optical paths between given nodes. When an optical path computation for using spectral inversion between a given source node and a given destination node is desired, the pre-calculated values may be concatenated for improved computational efficiency.