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
Abstract
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.