Optical Channel Validation via Multi-Channel Impairment Evaluation
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Solution Overview
Problem
Optical communication networks face challenges in validating communication paths due to single-channel and multi-channel impairments, which affect the feasibility and performance of channels over time, especially in mesh topologies like DWDM networks, where existing channels can impact new channel establishment and quality.
Innovation Solution
The system and method for validating optical paths in optical communication networks account for single-channel and multi-channel impairments by translating these effects into impairment margins, using a signaling protocol to distribute and update cross-talk margins across network nodes, ensuring that new channels can be established while maintaining specified performance and minimizing impact on existing channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-channel impairment evaluation is performed to validate optical paths, then channel routing quality and QoS are improved, but computational complexity and validation time increase
Solution Approach 1:
The validation process is segmented into two distinct evaluation stages: single-channel impairment evaluation and multi-channel impairment evaluation. This segmentation allows the system to first assess individual channel characteristics independently, then evaluate inter-channel interactions separately, reducing the overall computational complexity while maintaining comprehensive validation quality.
Solution Approach 2:
Single-channel impairment evaluation is performed as a preliminary action before multi-channel impairment evaluation. By pre-assessing individual channel parameters and characteristics, the system establishes a baseline that simplifies the subsequent multi-channel analysis, reducing the computational burden of the more complex validation process.
2Adaptability or versatility
If impairment margins are dynamically updated and distributed across network nodes, then adaptability to traffic pattern changes is improved, but network signaling overhead increases
Solution Approach 1:
The impairment margin data structure is designed to serve multiple functions simultaneously: it characterizes single-channel impairments, evaluates multi-channel interactions, and provides validation criteria for path establishment. This multi-functionality reduces the need for separate signaling mechanisms, thereby reducing overall signaling overhead while maintaining comprehensive adaptability.
Solution Approach 2:
Impairment margin information is distributed and copied across multiple network nodes along the optical path. Each node receives and stores relevant impairment margin data for validation purposes, eliminating the need for continuous centralized querying and reducing signaling overhead while maintaining real-time adaptability to traffic changes.
3Reliability
If both single-channel and multi-channel impairments are considered in path validation, then channel performance reliability is improved, but validation processing time increases
Solution Approach 1:
The validation process is divided into sequential segments: single-channel impairment evaluation followed by multi-channel impairment evaluation. This segmentation allows each evaluation type to be processed independently with optimized algorithms, reducing total validation time while ensuring both single-channel and multi-channel performance requirements are met.
Solution Approach 2:
Single-channel impairment parameters are evaluated and stored as preliminary results before multi-channel evaluation begins. These pre-computed single-channel metrics serve as input for the multi-channel analysis, avoiding redundant calculations and reducing overall validation processing time while maintaining comprehensive performance assessment.
Data Source
AI summary
In an optical communication network that includes a plurality of interconnected network nodes, a method includes storing in each network node one or more cross-talk margins of respective communication channels that traverse the node. A potential communication channel that traverses a subset of the nodes in the network is identified. A quality of the potential communication channel is evaluated by processing the cross-talk margins stored in the nodes in the subset.