Optical Power Management via Digital Twin Simulation
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Solution Overview
Problem
Optical communication networks, such as DWDM networks, face inefficiencies in monitoring and maintenance due to various optical impairments like self-phase modulation, cross-phase modulation, and fiber nonlinear interference, which can degrade signal transmission and interfere with other channels, making power management complex and risky.
Innovation Solution
A method and system utilizing a digital twin of the optical communication network to model components and simulate network configurations, employing machine learning or heuristic algorithms to optimize optical power management by predicting performance levels and adjusting configurations to meet desired optimization criteria, thereby ensuring efficient power management without degrading existing services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standard monitoring systems are used to manage optical networks with numerous optical devices and communication lines, then the system structure remains simple, but the monitoring and maintenance efficiency deteriorates
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the optical network that replicates the physical network's structure, components, and operational parameters. This virtual model enables comprehensive monitoring and analysis without adding physical monitoring equipment to each optical device, thereby improving monitoring efficiency while avoiding proportional increases in system complexity
Solution Approach 2:
The digital twin system serves multiple functions simultaneously: it monitors network performance, simulates various scenarios, optimizes power management, and predicts potential failures. This multi-functional approach consolidates what would otherwise require separate systems into a single unified platform, improving productivity without linearly increasing complexity
2Reliability
If optical power adjustment is performed to improve signal transmission, then transmission performance improves, but the risk of interfering with other channels and degrading services increases
Solution Approach 1:
The system performs preliminary simulations of power adjustment scenarios in the digital twin environment before applying changes to the physical network. This advance testing identifies potential inter-channel interference and service degradation risks, allowing operators to optimize power settings while avoiding harmful effects on other channels
Solution Approach 2:
The digital twin continuously receives operational data from the physical network and provides feedback on the effects of power adjustments. This closed-loop feedback mechanism enables real-time optimization while automatically detecting and preventing interference with other channels, thereby improving transmission performance without causing service degradation
3Reliability
If comprehensive monitoring of optical impairments is implemented to improve service quality, then signal transmission quality improves, but the complexity of operation and maintenance increases
Solution Approach 1:
The digital twin replicates the complex optical network environment and all its impairments in a virtual space, allowing comprehensive monitoring and analysis without requiring complex physical monitoring equipment at each node. This virtual replication enables thorough service quality assessment while keeping the physical system relatively simple
Solution Approach 2:
The digital twin acts as an intermediary layer between the physical optical network and the operation/maintenance personnel. It processes complex impairment data, simulates various scenarios, and presents simplified recommendations, thereby improving service quality monitoring while reducing the complexity faced by operators
Data Source
AI summary
System and method for optimizing optical power management along one or more optical channels of an optical communication network (OCN), the OCN comprising a plurality of optical channels. The method comprises accessing a digital twin (DT) of the OCN, receiving a desired optimization instruction to optimize the one or more optical channels in view of at least one operational parameter, executing an optical power optimization module on the DT by simulating application of at least one network configuration of the at least one optical channel, each network configuration having a corresponding predicted optimized level indicative of expected performances of the at least one optical channel of the OCN for the corresponding network configuration. In response to the predicted optimization level of a given network configuration satisfying a criterion, the network configuration is identified as a target network configuration and applied on the OCN.