A new method of using deep neural network to compensate PDL

Kan Li; Danshi Wang; Shengchen Li

doi:10.1117/12.2522573

14 February 2019 A new method of using deep neural network to compensate PDL

Kan Li, Danshi Wang, Shengchen Li

Proceedings Volume 11048, 17th International Conference on Optical Communications and Networks (ICOCN2018); 110481T (2019) https://doi.org/10.1117/12.2522573
Event: 17th International Conference on Optical Communications and Networks (ICOCN2018), 2018, Zhuhai, China

Abstract

We proposed a new method using DNN to compensate the damage caused by PDL. The scenario this experiment used is 16-QAM signals transmitted at 2x28 GBaud rate in a polarization-division multiplexing system. A DNN is proposed to compensate for the damage caused by PDL. The result shows that, BER of the system is reduced to 1e-3, and the damage caused by PDL can be minimized in the polarization multiplexed optical fiber communication system within 600 km.

Citation Download Citation

Kan Li, Danshi Wang, and Shengchen Li "A new method of using deep neural network to compensate PDL", Proc. SPIE 11048, 17th International Conference on Optical Communications and Networks (ICOCN2018), 110481T (14 February 2019); https://doi.org/10.1117/12.2522573

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