Optical Network Capacity Mining via Software-Defined Modulation

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Solution Overview

Problem

Optical networks face challenges in efficiently managing capacity and scheduling services due to the complexity of hardware-defined networks, which limits the ability to optimize capacity without additional hardware and schedule intermittent services across multiple layers effectively.

Innovation Solution

The implementation of a user interface for real-time capacity mining and scheduling in photonic networks, allowing operators to explore available excess capacity and orchestrate changes in the optical network with minimal user intervention, using software-defined approaches to adjust modulation formats and spectral allocation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If hardware-defined networks are used, then network stability is maintained, but capacity optimization and service scheduling flexibility are limited

Engineering Contradiction:

Improvecapacity optimization flexibilityVSAvoidnetwork control complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent replaces hardware-defined network configurations with software-defined approaches. The optical network manager uses software to dynamically adjust modulation formats, spectral allocation, and capacity parameters without requiring physical hardware changes. This substitution enables flexible capacity optimization while maintaining network stability through centralized software control.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system implements dynamic capacity mining and service scheduling through software that continuously monitors network conditions and adjusts parameters in real-time. The optical network manager dynamically modifies modulation formats (e.g., from QPSK to 16QAM), spectral masks, and power settings based on current traffic demands and network state, transforming static hardware configurations into adaptive software-controlled systems.

Inventive Principle:

Principle #15Dynamics

2Quantity of substance

If additional hardware is deployed to increase capacity, then network capacity is improved, but cost and device complexity increase

Engineering Contradiction:

Improvenetwork capacityVSAvoidhardware infrastructure complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent extracts excess capacity by changing operational parameters of existing optical modems without adding hardware. The system adjusts modulation formats (e.g., transitioning from DP-QPSK to DP-16QAM), spectral allocation, power settings, and other parameters to increase capacity utilization. This allows the network to handle more traffic using the same physical infrastructure, avoiding the need for additional hardware deployment.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system creates virtual copies of network capacity through software-defined configurations. By implementing multiple modulation formats and spectral allocations in software, the network can provide multiple capacity levels from the same physical modems, effectively copying capacity without duplicating hardware. The optical network manager can switch between different virtual capacity configurations based on demand.

Inventive Principle:

Principle #26Copying

3Quantity of substance

If optical margin is reduced to increase capacity, then capacity mining is enabled, but network reliability decreases

Engineering Contradiction:

Improveavailable capacityVSAvoidoptical signal reliability

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The system dynamically adjusts optical margin based on real-time network conditions and traffic priorities. The optical network manager continuously monitors signal quality, error rates, and traffic demands, adjusting modulation formats and power settings to maintain optimal margin levels. During normal operations, the system maintains higher margins for reliability, while during peak demands or for lower-priority traffic, it can temporarily reduce margins to increase capacity utilization.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent applies different margin levels to different network segments, services, or traffic flows based on their specific requirements. Critical services maintain higher optical margins for reliability, while non-critical services or during off-peak periods can operate with reduced margins to maximize capacity. The system can also apply different margins to different wavelengths or spatial divisions within the same physical network.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11914855B2Methods and systems for managing optical network services including capacity mining and scheduling

Publication Date: 2024.02.27 CIENA CORP

AI summary

Systems and methods include providing a user interface visualizing a current state of an optical network; receiving user inputs related to capacity mining in the optical network; determining a future state with the capacity mining based on the user inputs; and providing the user interface visualizing the future state. The future state can be presented with respect to a failed link and restoration of traffic on the failed link. The future state can include a plurality of plans with a visualization showing how much of the traffic is restored based on different approaches to the capacity mining. The capacity mining can include configuring optical modems based on determined available excess capacity.