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Subtraction-Clustering-Based Modulation Format Identification in Stokes Space
IEEE Photonics Technology Letters, 2017A Stokes-space-based modulation format identification (MFI) technique with low complexity is proposed for coherent optical receivers, on the basis of the subtraction clustering algorithm. Successful MFI with good optical signal-to-noise ratio performance can be realized among polarization-multiplexed BPSK, QPSK, 8PSK, 8QAM, and 16QAM signals ...
Pengyu Chen +4 more
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Modulation Format Identification in Coherent Receivers Using Deep Machine Learning
IEEE Photonics Technology Letters, 2016We propose a novel technique for modulation format identification (MFI) in digital coherent receivers by applying deep neural network (DNN) based pattern recognition on signals’ amplitude histograms obtained after constant modulus algorithm (CMA) equalization.
Khan, FN +5 more
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Relative entropy-based modulation format identification for coherent optical communication system
Optical Engineering, 2021Modulation format identification (MFI) is widely used in elastic optical networks, such as optical performance monitoring and signal compensation. We propose an MFI scheme, through extraction of the amplitude probability distribution feature of the received signals and an analysis of the relative entropy, which is also known as the Kullback–Leibler ...
Peng Zhou, Ye Lu, Dong Chen, Chuanqi Li
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Blind Shaping Rate Identification for Probabilistic Shaping Quadrature Amplitude Modulation Formats
Asia Communications and Photonics Conference/International Conference on Information Photonics and Optical Communications 2020 (ACP/IPOC), 2020We experimentally demonstrate a blind scheme enabled by a frequency offset loading technique to identify the shaping factor and modulation format of probabilistically shaped 16/64/256QAM signals with various entropies.
Zexin Chen +5 more
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Robust and Blind Modulation Format Identification for Elastic Optical Networks
2018 European Conference on Optical Communication (ECOC), 2018We propose and experimentally demonstrate a novel modulation format identification method based on intensity fluctuation features. It is robust to both linear and nonlinear noise and capable of recognizing mainstream modulation formats (4-/8-/16-/32-QAM) with above 99.8% overall identification accuracies.
Lin Jiang +7 more
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Modulation Format Identification Using Support Vector Machine in Heterogeneous Optical Networks
Asia Communications and Photonics Conference 2016, 2016A simple and effective method for modulation format identification (MFI) using a support vector machine (SVM) trained with the features extracted from the asynchronous amplitude histogram(AAH) in next-generation heterogeneous optical networks is proposed.
Min Zhang +5 more
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Modulation format identification Based on PCA and ADTS in Optical Communication
Asia Communications and Photonics Conference, 2017We realize the identification of commonly-used modulation formats including 4QAM, 16QAM and 64QAM by using the principal component analysis (PCA) and asynchronous delay-tap sampling (ADTS).
Jiadelaguli Biekesutan +4 more
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Blind Modulation Format Identification Based on Fourier Fitting for Coherent Receivers
2018 23rd Opto-Electronics and Communications Conference (OECC), 2018Blind modulation format identification based on Fourier series fitting to identify the unique features in one-dimensional vector is proposed and verified. It is able to identify the mainstream modulation formats with low complexity.
Lin Jiang +6 more
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Efficient Modulation Format Identification Using Transfer Learning
2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), 2022Dhirendra Kumar Jha, Jitendra K. Mishra
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Low-Complexity and Nonlinearity-Tolerant Modulation Format Identification Using Random Forest
IEEE Photonics Technology Letters, 2019A novel low-complexity and nonlinearity-tolerant modulation format identification (MFI) using random forest (RF) is proposed for the flexible coherent receivers (FCRs). The RF-based MFI takes the advantage of distinct features from the amplitude histograms (AHs) and the swarm intelligence of RF to significantly reduce the computational complexity ...
Yan Zhao +6 more
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