相干光传输系统中基于神经网络的非线性抑制均衡器的FPGA实现

2022 European Conference on Optical Communication (ECOC) Pub Date : 2022-06-24 DOI:10.48550/arXiv.2206.12180

Pedro J. Freire, M. Anderson, B. Spinnler, T. Bex, J. Prilepsky, T. Eriksson, N. Costa, W. Schairer, Michaela Blott, A. Napoli, S. Turitsyn

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引用次数: 6

摘要

首次在FPGA中实现了基于循环和前馈神经网络的非线性补偿均衡器，其复杂性可与色散均衡器相媲美。我们证明了基于神经网络的均衡器可以优于每跨1步的DBP。

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Towards FPGA Implementation of Neural Network-Based Nonlinearity Mitigation Equalizers in Coherent Optical Transmission Systems

For the first time, recurrent and feedforward neural network-based equalizers for nonlinearity compensation are implemented in an FPGA, with a level of complexity comparable to that of a dispersion equalizer. We demonstrate that the NN-based equalizers can outperform a 1-step-per-span DBP.

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2022 European Conference on Optical Communication (ECOC)

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