Optical Channel Validation via Multi-Channel Impairment Evaluation
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Solution Overview
Problem
Optical communication networks face challenges in validating communication channels due to multi-channel impairments, which affect the performance of channels and change over time with shifting traffic patterns, leading to suboptimal channel routing and Quality of Service (QoS).
Innovation Solution
The system evaluates and validates optical paths by considering single-channel and multi-channel impairments, translating these into impairment margins that account for cross-talk, OSNR, PMD, and filtering, using local databases and signaling protocols to propagate and distribute these margins across network nodes, allowing for better channel routing and QoS.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-channel impairment evaluation is implemented, then channel validation accuracy and QoS improve, but system complexity and computational requirements increase
Solution Approach 1:
The patent segments the channel validation process into distinct impairment evaluation components (cross-talk, OSNR, PMD, filtering) that can be independently calculated and aggregated. Each impairment type is evaluated separately using specific formulas, allowing the complex multi-channel evaluation to be broken down into manageable segments that improve accuracy without overwhelming system complexity.
Solution Approach 2:
The system performs preliminary impairment evaluations by pre-calculating impairment margins for each channel based on network configuration and traffic patterns. These preliminary evaluations are stored and updated periodically, allowing the system to account for multi-channel effects without performing real-time complex calculations for every routing decision, thus balancing accuracy with computational efficiency.
2Productivity
If impairment margins are propagated across all network nodes, then channel routing optimization improves, but signaling overhead and processing time increase
Solution Approach 1:
Each network node maintains local impairment margin information specific to its connected channels and evaluates impairments locally based on its configuration. Instead of centralized evaluation, nodes independently calculate their local impairment contributions and propagate only relevant margin information to adjacent nodes, reducing overall signaling overhead while maintaining routing optimization capability.
Solution Approach 2:
The system propagates impairment margin information selectively rather than comprehensively - only the necessary margin data required for routing decisions is exchanged between nodes. This partial action approach provides sufficient information for effective channel routing without the excessive signaling overhead of complete impairment data exchange, optimizing the balance between routing efficiency and processing time.
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, and for each communication channel that traverses the node, one or more impairment margins of respective impairments that affect the communication channel. 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 impairment margins stored in the nodes in the subset.