Transmitter Laser Frequency Offset Estimation Based on Artificial Neural Network for Coherent Optical Systems

Haobo Xu; Zhiqun Zhai; Hexun Jiang; Lilin Yi; Weisheng Hu; Qunbi Zhuge

doi:10.1364/SPPCOM.2021.SpM5C.4

OSA Advanced Photonics Congress 2021
OSA Technical Digest (Optica Publishing Group, 2021),
paper SpM5C.4
•https://doi.org/10.1364/SPPCOM.2021.SpM5C.4

Transmitter Laser Frequency Offset Estimation Based on Artificial Neural Network for Coherent Optical Systems

Haobo Xu, Zhiqun Zhai, Hexun Jiang, Lilin Yi, Weisheng Hu, and Qunbi Zhuge

Signal Processing in Photonic Communications 2021

Washington, DC United States
26–29 July 2021
ISBN: 978-1-943580-94-1

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Neural Networks Applications for Photonic Systems (SpM5C)

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H. Xu, Z. Zhai, H. Jiang, L. Yi, W. Hu, and Q. Zhuge, "Transmitter Laser Frequency Offset Estimation Based on Artificial Neural Network for Coherent Optical Systems," in OSA Advanced Photonics Congress 2021, B. Yang, F. Leo, A. Tauke-Pedretti, S. Arafin, M. Clerici, L. Caspani, L. Busse, M. Kats, J. Fan, W. Ming (Steve) Lee, D. Caplan, N. Parsons, W. Freude, C. Tremblay, D. Hillerkuss, K. Igarashi, H. Elgala, N. Guerrero Gonzalez, R. "Patty" Stabile, K. Jaeger, R. Saive, H. Aziz, and H. Tan, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper SpM5C.4.

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Abstract

We propose a machine learning based scheme to estimate transmitter laser frequency offset, which is a nonnegligible factor affecting the performance of transceiver-joint equalization. The estimation error is less than 0.05 GHz.

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