Paper
12 December 2018 Artificial neural network based link OSNR estimation with a network approach
Author Affiliations +
Proceedings Volume 10849, Fiber Optic Sensing and Optical Communication; 1084912 (2018) https://doi.org/10.1117/12.2505502
Event: International Symposium on Optoelectronic Technology and Application 2018, 2018, Beijing, China
Abstract
The performance monitoring of fiber-optics communication is an important task in nowadays communication system. Link optical noise-to-signal ratio (OSNR) is one of the most important parameters that affect the performance of optical networks. The traditional internal measurement method may increase the network construction cost and operation complexity. To overcome these drawbacks, an ANN based link OSNR estimation method with external measurement is proposed in this paper. Route level OSNR values are measured at the edge nodes and are used for link level OSNR estimation with the trained ANN. Besides, a heuristic method for route set generation is proposed to generate the route set that introduce fewer extra network load. The experiment results demonstrate that the ANN based method can meet the practical requirement in both estimation accuracy and computation complexity. The proposed method can be an important part of optical network OSNR monitoring to ensure robust and intelligent network operation.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zeyuan Yang, Rentao Gu, Dajiang Wang, Yanxia Tan, Hongbiao Li, and Yuefeng Ji "Artificial neural network based link OSNR estimation with a network approach", Proc. SPIE 10849, Fiber Optic Sensing and Optical Communication, 1084912 (12 December 2018); https://doi.org/10.1117/12.2505502
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KEYWORDS
Optical amplifiers

Neurons

Artificial neural networks

Optical networks

Interference (communication)

Networks

Signal to noise ratio

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