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

被引：0

作者：

Freire, Pedro J. ^{[1
]}

Anderson, Michael ^{[1
]}

Spinnler, Bernhard ^{[2
]}

Bex, Thomas ^{[2
]}

Prilepsky, Jaroslaw E. ^{[1
]}

Eriksson, Tobias A. ^{[3
]}

Costa, Nelson ^{[4
]}

Schairer, Wolfgang ^{[2
]}

Blott, Michaela ^{[5
]}

Napoli, Antonio ^{[2
]}

Turitsy, Sergei K. ^{[1
]}

机构：

[1] Aston Univ, Birmingham, W Midlands, England

[2] Infinera, Munich, Germany

[3] Infinera, Stockholm, Sweden

[4] Infinera, Lisbon, Portugal

[5] AMD Xilinx Inc, Dublin, Ireland

来源：

2022 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC) | 2022年

基金：

英国工程与自然科学研究理事会;

关键词：

D O I：

暂无

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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. (C) 2022 The Author(s)

引用

页数：4

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