Optical Network Margin-Based Capacity Optimization
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Solution Overview
Problem
Optical networks face inefficiencies due to conventional engineering methods that prioritize worst-case scenarios, leading to excess margin and underutilization of capacity, as they fail to adapt and optimize based on current conditions, unlike other communication systems.
Innovation Solution
Implementing a margin-based optimization system that uses Network Management Systems, Element Management Systems, and Software Defined Networking controllers to determine and adjust parameters such as power, modulation format, and spectral settings in real-time, optimizing capacity by consuming excess margin and adjusting wavelengths to increase bandwidth without increasing capital costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional worst-case engineering methods are used to ensure all wavelengths work under any conditions, then network reliability is improved, but capacity utilization deteriorates due to excess margin
Solution Approach 1:
The patent implements dynamic optimization of optical network parameters (modulation format, power levels, spectral settings) based on current network conditions rather than static worst-case design. The system continuously monitors and adjusts parameters to consume excess margin while maintaining reliability, transforming the network from a static to a dynamic operational state.
Solution Approach 2:
The system changes multiple optical parameters simultaneously (modulation format, launch power, spectral width, guard bands) to optimize capacity. By adjusting these parameters based on current conditions and available margin, the system increases capacity utilization without compromising the fundamental reliability requirements.
2Productivity
If advanced optical modems with adaptable modulation formats are deployed, then capacity potential is improved, but system complexity worsens
Solution Approach 1:
The optical modems perform self-optimization by automatically adjusting their modulation formats and parameters based on current network conditions and available margin. This self-service capability reduces the need for complex external control systems while maximizing capacity potential through adaptive modulation.
Solution Approach 2:
The system implements feedback mechanisms where optimization results from one wavelength or channel inform adjustments to other wavelengths. The margin-based optimization uses feedback from network performance monitoring to continuously refine parameter settings, enabling complex adaptability through systematic feedback loops.
3Reliability
If optimization is performed for full set of wavelengths to account for nonlinear interactions, then network reliability is improved, but optimization time and computational resources worsen
Solution Approach 1:
The optimization process is segmented into manageable components, optimizing wavelengths in groups or individually based on their interaction levels. This segmentation allows the system to account for nonlinear interactions where necessary while reducing computational burden by not treating all wavelengths uniformly, thus balancing reliability with optimization time.
Solution Approach 2:
The system performs partial optimization by focusing computational resources on wavelengths with significant margin or high interaction levels, rather than exhaustively optimizing all wavelengths equally. This approach consumes sufficient computational effort to ensure reliability for critical wavelengths while avoiding excessive optimization time on less critical channels.
Data Source
AI summary
A computer-implemented method is implemented in one of a Network Management System (NMS), an Element Management System (EMS), a Software Defined Networking (SDN) controller, and a server executing an SDN application, to increase capacity of one or more links in an optical network. The computer-implemented method includes determining Net System Margin comprising a metric of overall excess margin in the optical network until a Forward Error Correction (FEC) limit is reached; performing an optimization of a plurality of parameters of the optical network to determine which settings are appropriate in the optical network to provide the increased capacity and to consume at least part of the Net System Margin; and causing a plurality of modems in the optical network to change settings based on the optimization to provide the increased capacity.