Presentation Information
[TuP-B-9]Low-Complexity and Rapid-Adaptive Neural Network Equalizer based on SkipNet for High-Speed Optical IM/DD Communication System
○Chengxi Wang1, Zhongya Li1, An Yan1, Junhao Zhao1, Yingjun Zhou1, Jianyang Shi1, Nan Chi1, Zhixue He2, Junwen Zhang1 (1Fudan Univ., 2Pengcheng Laboratory)
Keywords:
Artificial intelligence and machine learning for optical transmission systems and subsystems,Digital signal processing algorithms for optical communications
We propose and demonstrate a low-complexity and rapid-adaptive neural network equalizer based on SkipNet for high-speed optical IM/DD system, achieving 300- and 270-Gbps data transmission under B2B and 1-km fiber with improved sensitivity and data-rates.