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Artificial Neural Network Based Link OSNR Estimation with a Network Approach

机译:基于人工神经网络的网络方法基于链接OSNR估计

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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.
机译:光纤通信的性能监控是如今通信系统中的重要任务。链路光学噪声到信号比(OSNR)是影响光网络性能的最重要参数之一。传统的内部测量方法可能会增加网络施工成本和操作复杂性。为了克服这些缺点,本文提出了一种基于ANN的链路OSNR估计方法,包括外部测量。路由级OSNR值在边缘节点上测量,并用于与培训的ANN的链路级别OSNR估计。此外,提出了一种用于路线集生成的启发式方法,以生成引入额外网络负载的路由集。实验结果表明,基于ANN的方法可以满足估计精度和计算复杂性的实际要求。所提出的方法可以是光网络OSNR监控的重要组成部分,以确保坚固且智能的网络操作。

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