Modulation Scheme Identification Based on Artificial Neural Network Algorithms for Optical Communication System

Jalil, Mustafa A.; Ayad, Jenan; Abdulkareem, Hanan J.

doi:10.5614/itbj.ict.res.appl.2020.14.1.5

Cited by 8 publications

(1 citation statement)

References 17 publications

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“…The method is based on the amplitude variance. In [11][12][13][14], an MFI method based on the artificial neural network utilizes amplitude histograms (AHs) as the recognition feature. In [15], a CNN-based cost-effective MFI method is proposed.…”

Section: Introductionmentioning

confidence: 99%

Joint Modulation Format Identification and Optical Signal-to-Noise Ratio Monitoring Based on Ternary Neural Networks

Zhou

Chen

et al. 2022

IEEE Access

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Modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring are essential for elastic optical networks. A method for joint modulation format identification and OSNR monitoring based on ternary neural networks was proposed. Further, a ternary neural network was established, and the constellation images after constant modulus algorithm (CMA) equalization were used as input features. Four commonly used modulation formats were distinguished, including dual-polarization (DP)-QPSK, 8QAM, 16QAM, and 64QAM. A 32G baud simulation system was constructed, and the results were analyzed. First, we investigated the influence of resolution and sample length on the identification accuracy. The values 32 and 7000 were selected for the two parameters, respectively, based on the balance between resource consumption and accuracy. Then, we compared the performance of the binary neural network (BNN), ternary neural network (TNN), and full-precision neural network (FNN). The results indicate that the memory consumption and extraction time of the TNN are similar to those of the BNN, and the accuracy is further improved. Moreover, the robustness of the system was analyzed. The results validate that the proposed method can tolerate fiber nonlinearity (from 500 km to 1500 km). Finally, an experiment was conducted to prove the practicality of the proposed method.INDEDX TERMS Modulation format identification (MFI), optical signal-to-noise ratio (OSNR) monitoring, ternary neural network (TNN), optical fiber communication.

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Section: Introductionmentioning

confidence: 99%