Optical Network Digital Twin -- Practical Use Cases and Architecture

TL;DR

This paper presents a practical architecture for an Optical Network Digital Twin that supports dynamic, AI-driven operation and optimization, addressing current deployment challenges.

Contribution

It introduces a novel digital twin architecture tailored for optical networks, including use cases and key challenges for real-world deployment.

Findings

Proposes a digital twin architecture enabling AI-driven optical network management.

Demonstrates use cases like operator optimization and multi-operator interconnection.

Identifies key challenges for practical deployment of optical network digital twins.

Abstract

With the widespread adoption of AI, machine-to-machine communications are rapidly increasing, reshaping the requirements for optical networks. Recent advances in Gaussian noise modeling for digital coherent transmission have raised expectations for digital-twin-based operation. However, unlike digital twins in wireless communication, which are already well established, significant barriers remain for commercialization in optical networks. This paper discusses the evolving requirements of optical networks in the AI era and proposes a practical Optical Network Digital Twin architecture enabling dynamic and Quality of Transmission aware operation beyond conventional management. Representative use cases, including operator-driven optimization, user-operator collaboration, and multi-operator interconnection, are presented, along with the architectural framework and key challenges toward practical deployment.