Journal article
Cascade recurrent neural network-assisted nonlinear equalization for a 100 Gb/s PAM4 short-reach direct detection system.
Zhaopeng Xu, Chuanbowen Sun, Tonghui Ji, Jonathan H Manton, William Shieh
Optics Letters | Optical Society of America | Published : 2020
DOI: 10.1364/OL.394048
Abstract
We propose a novel, to the best of our knowledge, cascade recurrent neural network (RNN)-based nonlinear equalizer for a pulse amplitude modulation (PAM)4 short-reach direct detection system. A 100 Gb/s PAM4 link is experimentally demonstrated over 15 km standard single-mode fiber (SSMF), using a 16 GHz directly modulated laser (DML) in C-band. The link suffers from strong nonlinear impairments which is mainly induced by the mixture of linear channel effects with square-law detection, the DML frequency chirp, and the device nonlinearity. Experimental results show that the proposed cascade RNN-based equalizer outperforms other feedforward or non-cascade neural network (NN)-based equalizers ow..
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Awarded by Australian Research Council
Funding Acknowledgements
Australian Research Council (DP150101864, DP190103724).