Compensation of nonlinear distortion in coherent optical OFDM systems using a MIMO deep neural network-based equalizer - Aldaya, Ivan [UNESP]; Giacoumidis, Elias; Tsokanos, Athanasios; Jarajreh, Mutsam; Wen, Yannuo; Wei, Jinlong; Campuzano, Gabriel; Abbade, Marcelo L. F. [UNESP]; Barry, Liam P. (Optical Soc Amer, 2020)
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