基于动态更新数字孪生的光网络生命周期管理:一种混合数据驱动和物理信息的方法

Yuchen Song;Min Zhang;Yao Zhang;Yan Shi;Shikui Shen;Xiongyan Tang;Shanguo Huang;Danshi Wang
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引用次数: 0

摘要

数字孪生(DT)技术被提出用于下一代光网络的自主运行和生命周期管理。为了充分利用潜在容量并适应动态业务,DT必须在其整个生命周期内与已部署的光网络同步动态更新,以确保低利润运营。本文提出了一种用于光网络生命周期管理的动态更新DT,采用一种混合方法,将数据驱动和物理信息技术集成到光纤通道建模中。这种集成确保了光学性能预测的快速计算速度和高物理一致性,同时实现了DT关键物理参数的动态更新。通过大规模网络仿真,论证了光网络的生命周期管理,包括网络部署时的准确性能预测和网络运行时的动态更新。与传统数值方法相比,预测速度可提高100倍。此外,光纤拉曼增益强度、放大器频率相关增益曲线以及C和L波段光纤与放大器之间的连接器损耗可以同时更新。此外,在现场试验的C+ l波段传输链路上验证了动态更新DT,在设备更换后的性能估计中实现了1.4 dB的最大精度提高。总体而言,动态更新DT有望推动下一代光网络实现生命周期自主管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lifecycle Management of Optical Networks With Dynamic-Updating Digital Twin: A Hybrid Data-Driven and Physics-Informed Approach
Digital twin (DT) techniques have been proposed for the autonomous operation and lifecycle management of next-generation optical networks. To fully utilize potential capacity and accommodate dynamic services, the DT must dynamically update in sync with deployed optical networks throughout their lifecycle, ensuring low-margin operation. This paper proposes a dynamic-updating DT for the lifecycle management of optical networks, employing a hybrid approach that integrates data-driven and physics-informed techniques for fiber channel modeling. This integration ensures both rapid calculation speed and high physics consistency in optical performance prediction while enabling the dynamic updating of critical physical parameters for DT. The lifecycle management of optical networks, covering accurate performance prediction at the network deployment and dynamic updating during network operation, is demonstrated through simulation in a large-scale network. Up to 100 times speedup in prediction is observed compared to classical numerical methods. In addition, the fiber Raman gain strength, amplifier frequency-dependent gain profile, and connector loss between fiber and amplifier on C and L bands can be simultaneously updated. Moreover, the dynamic-updating DT is verified on a field-trial C+L-band transmission link, achieving a maximum accuracy improvement of 1.4 dB for performance estimation post-device replacement. Overall, the dynamic-updating DT holds promise for driving the next-generation optical networks towards lifecycle autonomous management.
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