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

Author(s)

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

• Document type: Journal article
• Source: OPTICS LETTERS; v. 45, n. 20, p. 4-pg., 2020-10-15.

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. (C) 2020 Optical Society of America (AU)

• FAPESP's process: 18/25339-4 - Integrated photonics devices
• Grantee: Newton Cesario Frateschi
• Support Opportunities: Research Projects - Thematic Grants