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

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

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)5820-5823
Number of pages4
JournalOptics Letters
Volume45
Issue number20
DOIs
Publication statusPublished - 15 Oct 2020

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