基于CNN-LSTM和海马优化算法的二阶拉曼光纤放大器设计方案
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作者单位:

西安邮电大学

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中图分类号:

060.2330; 060.4370; 060.4510

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


Second-order Raman fiber amplifier design scheme based on CNN-LSTM and sea horse optimization algorithm
Author:
Affiliation:

1.Xi’an University of Posts &2.amp;3.Telecommunications;4.Xi'an University of Posts and Telecommunications

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    随着通信系统向高速率、超带宽不断发展,适应这种发展的高性能拉曼放大器的设计逐渐成为研究重点。然而,由于输出拉曼增益、噪声和泵浦参数之间复杂的非线性关系,设计高性能的拉曼放大器具有挑战性。传统的数值优化方法在解决这个问题上效率不佳。为了解决这个问题,本文提出了一个使用卷积神经网络和长短期记忆网络的二阶拉曼光纤放大器增益和噪声预测模型。本研究的目的是研究不同预测模型性能对设计拉曼光纤放大器的影响,并利用海马算法优化模型,以准确反映泵浦参数、光纤长度和目标增益和噪声分布之间的映射关系。实验结果表明,本文提出的模型在增益和噪声预测方面的均方根误差分别只有0.0431和0.0224 dB,预测值和目标值之间的误差小于0.25 dB,平均耗时小于0.1337 s。该设计方案为未来拉曼光纤放大器的快速设计提供了方法和思路。

    Abstract:

    With the continuous development of communication systems towards high speed and ultra-bandwidth, the design of high-performance Raman amplifiers adapted to this development has gradually become a research focus. However, designing high-performance Raman amplifiers is challenging due to the complex non-linear relationship between output Raman gain, noise, and pump parameters. Traditional numerical optimization methods are not efficient in solving this problem. To address this, this paper proposes a second-order Raman fiber amplifier gain and noise prediction model using Convolutional Neural Network and Long-Short Term Memory. The aim of this study is to investigate the impact of different prediction model performances on the design of Raman fiber amplifiers, and to optimize the model using the hippocampus algorithm to accurately reflect the mapping relationship between pump parameters, fiber length, and the target gain and noise distribution. Experimental results show that the proposed model has a Root Mean Square Error of only 0.0431 and 0.0224 dB in gain and noise prediction, with an error between the predicted and target values below 0.25 dB and an average consumption time of less than 0.1337 s. This design provides methods and ideas for the rapid design of Raman fiber amplifiers in the future.

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  • 收稿日期:2023-03-10
  • 最后修改日期:2023-06-19
  • 录用日期:2023-06-27
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