Nonlinear Fiber Compensation Based on Neural Network in Reflective Coherent Detection System

We study artificial neural network used for fiber nonlinear mitigation in single-fiber bidirectional reflective coherent detection system. In this system, the transmitter of this system is located at the receiving end, and the transmission distance of carrier is double the length of actual optical f...

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Bibliographic Details
Published in2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) pp. 1364 - 1367
Main Authors Bi, Chengqi, Chen, Shuqiang, Fu, Jiacheng
Format Conference Proceeding
LanguageEnglish
Published IEEE 09.04.2021
Subjects
Adaptive optics
artificial neural network
bidirectional single fiber
Coherence
Fiber nonlinear optics
Integrated optics
nonlinear effect
Optical computing
Optical fiber networks
Optical fibers
reflective coherent detection system
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Summary:We study artificial neural network used for fiber nonlinear mitigation in single-fiber bidirectional reflective coherent detection system. In this system, the transmitter of this system is located at the receiving end, and the transmission distance of carrier is double the length of actual optical fiber channel, the required optical emission power increases which leads to intensifying of nonlinear effect. Also, using neural network to compensate fiber nonlinear can be processed without knowing the system parameters preferentially. The simulation results show that fiber nonlinear mitigation based on neural network can effectively reduce the bit error rate and improve the transmission performance of the system.
DOI:10.1109/ICSP51882.2021.9408701