A novel in-band OSNR monitor is proposed and experimentally demonstrated for WDM signal. By using a Lyot-Sagnac interferometer, the monitor realized OSNR measurement from 7.5~25 dB (within an accuracy of ± 0.5 dB) for 4-channel 40 Gbaud NRZ-QPSK signals, without requirement for prior knowledge of the noise-free coherence properties of signal. Further investigation proved that this OSNR monitor had high tolerance to chromatic dispersion (0~1152 ps/nm), first-order polarization mode dispersion (0~100 ps), and polarized noise. Moreover, the monitor worked very well even with input optical power as low as -8.24 dBm, and also worked in in C-band. Theoretical analysis and experimental results prove that it is capable of measuring OSNR for polarization-division-multiplexing signals.
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http://dx.doi.org/10.1364/OE.23.020257 | DOI Listing |
Modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring are important portions of optical performance monitoring (OPM) for future dynamic optical networks. In this paper, we proposed a fusion module few-shot learning (FMFSL) algorithm as an improvement upon the ordinary few-shot learning algorithms for image recognition with the specialty in adopting a combination of a dilated convolutional group and an asymmetric convolutional group to advance the feature extraction. FMFSL algorithm is applied in MFI and OSNR monitoring in coherent optical communication systems with its performance investigated in both back-to-back and fiber transmission scenarios using small-scale constellation diagrams.
View Article and Find Full Text PDFAn algorithm is proposed for few-shot-learning (FSL) jointing modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) estimation. The constellation diagrams of six widely-used modulation formats over a wide range of OSNR (10-40 dB) are obtained by a dual-polarization (DP) coherent detection system at 32 GBaud. We introduce auxiliary task to model-agnostic meta-learning (MAML) which makes the gradient of meta tasks decline faster in the direction of optimal target.
View Article and Find Full Text PDFOptical parameter estimation based on the data obtained by coherent optical receivers is critical for optical performance monitoring (OPM) and the stable operation of the receiver digital signal processing (DSP). A robust multi-parameter estimation is intricate due to the interference of various system effects. By resorting to the cyclostationary theory, we are able to formulate a chromatic dispersion (CD), frequency offset (FO), and optical signal-to-noise ratio (OSNR) joint estimation strategy that is resistant to the random polarization effect, including polarization mode dispersion (PMD) and polarization rotation.
View Article and Find Full Text PDFAn approach for simultaneous modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring in digital coherent optical communications is proposed based on optoelectronic reservoir computing (RC) and the signal's amplitude histograms (AHs) obtained after the adaptive post-equalization. The optoelectronic RC is implemented using a Mach-Zehnder modulator and optoelectronic delay feedback loop. We investigate the performance of the proposed model with the number of symbols, bins of AHs and the hyperparameters of optoelectronic RC.
View Article and Find Full Text PDFConvolutional neural network based transfer learning (TL) is proposed to achieve joint optical performance monitoring with bit rate and modulation format identification in optical communication systems. TL is used to improve the execution of various tasks by extracting features without knowing other optical link parameters. Eye diagrams of four different modulation formats are generated at optical signal-to-noise ratios (OSNRs) varying from 15 to 30 dB for two distinct bit rates, which are then identified simultaneously with a trained deep neural network.
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