Machine learning model based on the time domain regular perturbation-based theory for performance estimation in arbitrary heterogeneous optical links

IF 2.6 3区 计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Xiaoyan Ye , Amirhossein Ghazisaeidi
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引用次数: 0

Abstract

To meet the required high demands for the capacity of optical networks, there are several efforts in recent years to further reduce the system margin. To achieve this goal, a fast and reliable QoT estimation tool is needed. The key module of such QoT tool is the nonlinear interference variance estimation. This paper presents a novel machine learning tool to speed up the exact model by six orders of magnitude without scarifying the accuracy and the scalability of this semi-analytical model. Moreover, to further enhance the scalability of the model, we used the cross-correlation functions to re-write the equations. The proposed ML-based framework KerrNet, based on a bank of small ANNs, can handle any arbitrary heterogeneous link up to ten thousand km composed of different fiber span. The transmitting C-band WDM channels in both fully loaded and sparsely occupied configurations are evaluated. The crucial steps for the machine learning algorithm to converge, which are the data preparation and the choice of training data, are presented in detail.
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来源期刊
Optical Fiber Technology
Optical Fiber Technology 工程技术-电信学
CiteScore
4.80
自引率
11.10%
发文量
327
审稿时长
63 days
期刊介绍: Innovations in optical fiber technology are revolutionizing world communications. Newly developed fiber amplifiers allow for direct transmission of high-speed signals over transcontinental distances without the need for electronic regeneration. Optical fibers find new applications in data processing. The impact of fiber materials, devices, and systems on communications in the coming decades will create an abundance of primary literature and the need for up-to-date reviews. Optical Fiber Technology: Materials, Devices, and Systems is a new cutting-edge journal designed to fill a need in this rapidly evolving field for speedy publication of regular length papers. Both theoretical and experimental papers on fiber materials, devices, and system performance evaluation and measurements are eligible, with emphasis on practical applications.
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