Compensation of nonlinear distortion in coherent optical OFDM systems using a MIMO deep neural network-based equalizer

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2020-10-15

Autores

Aldaya, Ivan [UNESP]
Giacoumidis, Elias
Tsokanos, Athanasios
Jarajreh, Mutsam
Wen, Yannuo
Wei, Jinlong
Campuzano, Gabriel
Abbade, Marcelo L. F. [UNESP]
Barry, Liam P.

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Optical Soc Amer

Resumo

A novel nonlinear equalizer based on a multiple-input multiple-output (MIMO) deep neural network (DNN) is proposed and experimentally demonstrated for compensation of inter-subcarrier nonlinearities in a 40 Gb/s coherent optical orthogonal frequency division multiplexing system. Experimental results reveal that MIMO-DNN can extend the power margin by 4 dB at 2000 km of standard single-mode fiber transmission when compared to linear compensation or conventional single-input single-output DNN. It is also found that MIMO-DNN outperforms digital back propagation by increasing up to 1 dB the effective Q-factor and reducing by a factor of three the computational cost. (C) 2020 Optical Society of America

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Optics Letters. Washington: Optical Soc Amer, v. 45, n. 20, p. 5820-5823, 2020.

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