Presentation Information

2:30 PM - 2:45 PM JST(5:30 AM - 5:45 AM UTC)

[MB1-2]Dynamic complex deep Neural Network Nonlinear Equalizer for 64 QAM Long-haul Transmission Systems

〇Govind Sharan Yadav¹, Takehiro Tsuritani², Shohei Beppu², Hidenori Takahashi², Itsuro Morita², Kai-Ming Feng¹, Jhih-heng Yan¹ (¹National Tsing Hua Univ., Taiwan, ²KDDI Research Inc., Japan)

Keywords:

Digital signal processing techniques for optical communications,Complex Deep Artificial Neural Network,Deep Learning,Adaptive machine learning method

We implemented a two-hidden-layer dynamic complex deep neural network nonlinear equalizer which outperforms the linear equalizer, static and dynamic single hidden layer CDNN-NLE by 1.38-dB, 1.01-dB and 0.62-dB for a 34-GBaud/s, 64-QAM signal over 1200-km.

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