Optical power monitoring based on back propagation neural network algorithm

Yuchen Gao; Xuefang Zhang

doi:10.1117/12.3049815

18 November 2024 Optical power monitoring based on back propagation neural network algorithm

Yuchen Gao, Xuefang Zhang

Proceedings Volume 13398, Fourth International Conference on Optics and Communication Technology (ICOCT 2024); 133980H (2024) https://doi.org/10.1117/12.3049815
Event: Fourth International Conference on Optics and Communication Technology (ICOCT 2024), 2024, Nanjing, China

Abstract

In Dense Wavelength Division Multiplexing (DWDM) optical communication networks, the Optical Performance Monitor (OPM) can monitor key indicators for instance optical power, central wavelength, bandwidth, and optical signal-to-noise ratio in real-time. However, traditional OPM modules face the challenges like low accuracy, high cost, and unavoidable physical impacts. This paper proposes using the Back Propagation Neural Network (BPNN) algorithm to improve optical performance monitoring accuracy by reconstructing spectrum graphs to calculate optical power. Using simulated spectrum graphs as the dataset, the model is trained and validated with 0 dBm signals and evaluated with 5, 10, 15, and 20 dBm signals. Results show that the BPNN algorithm outperforms traditional OPM algorithm in reconstructing spectrum graph, improving optical power calculation accuracy and simplifying computational steps. With BPNN algorithm, the Mean Square Error (MSE) of the reconstructed spectrum is approximately 0.0011. This method not only enhances monitoring accuracy but also reduces errors in the OPM module. Although the training complexity increases, the prediction complexity has been decreased. Future research could optimize the structure and parameters of the BPNN model to improve its performance and explore its applicability in other optical communication systems.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuchen Gao and Xuefang Zhang "Optical power monitoring based on back propagation neural network algorithm", Proc. SPIE 13398, Fourth International Conference on Optics and Communication Technology (ICOCT 2024), 133980H (18 November 2024); https://doi.org/10.1117/12.3049815

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KEYWORDS

Neural networks

Education and training

Reconstruction algorithms

Data modeling

Cross validation

Neurons

Signal processing

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