The Experts below are selected from a list of 20283 Experts worldwide ranked by ideXlab platform
Alan Pak Tao Lau - One of the best experts on this subject based on the ideXlab platform.
-
joint osnr monitoring and Modulation Format identification in digital coherent receivers using deep neural networks
Optics Express, 2017Co-Authors: Faisal Nadeem Khan, Kangping Zhong, Xian Zhou, Waled Hussein Alarashi, Alan Pak Tao LauAbstract:We experimentally demonstrate the use of deep neural networks (DNNs) in combination with signals’ amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio (OSNR) monitoring and Modulation Format identification (MFI) in digital coherent receivers. The proposed technique automatically extracts OSNR and Modulation Format dependent features of AHs, obtained after constant modulus algorithm (CMA) equalization, and exploits them for the joint estimation of these parameters. Experimental results for 112 Gbps polarization-multiplexed (PM) quadrature phase-shift keying (QPSK), 112 Gbps PM 16 quadrature amplitude Modulation (16-QAM), and 240 Gbps PM 64-QAM signals demonstrate OSNR monitoring with mean estimation errors of 1.2 dB, 0.4 dB, and 1 dB, respectively. Similarly, the results for MFI show 100% identification accuracy for all three Modulation Formats. The proposed technique applies deep machine learning algorithms inside standard digital coherent receiver and does not require any additional hardware. Therefore, it is attractive for cost-effective multi-parameter estimation in next-generation elastic optical networks (EONs).
-
signal power distribution based Modulation Format identification for coherent optical receivers
Optical Fiber Technology, 2017Co-Authors: Jie Liu, Changjian Guo, Kangping Zhong, Zhenhua Dong, Alan Pak Tao LauAbstract:Abstract A simple Modulation Format identification (MFI) technique based on extracting features from the statistical distributions of normalized signal power is proposed for cognitive coherent optical receivers. The proposed MFI technique requires no prior training and is independent of phase noise or frequency offset. Furthermore, it also performs good identification of the polarization-multiplexed (PM) M-QAM signals even after insufficient equalization of the constant modulus algorithm (CMA). Simulation results demonstrate successful MFI among PM-QPSK, PM-8-QAM, PM-16-QAM, PM-32-QAM and PM-64-QAM signals within OSNR range of practical system. Experimental verification using PM-QPSK/16-QAM/64-QAM signals also confirms the feasibility of the proposed MFI technique after long distance fiber transmission.
-
Modulation Format identification in coherent receivers using deep machine learning
IEEE Photonics Technology Letters, 2016Co-Authors: Faisal Nadeem Khan, Kangping Zhong, Waled Hussein Alarashi, Alan Pak Tao LauAbstract:We 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. Experimental results for three commonly-used Modulation Formats demonstrate MFI with an accuracy of 100% over a wide optical signal-to-noise ratio (OSNR) range. The effects of fiber nonlinearity on the performance of MFI technique are also investigated. The proposed technique is non-data-aided (NDA) and avoids any additional hardware on top of standard digital coherent receiver. Therefore, it is ideal for simple and cost-effective MFI in future heterogeneous optical networks.
-
blind Modulation Format identification for digital coherent receivers
Optics Express, 2015Co-Authors: Syed Muhammad Bilal, Zhenhua Dong, Gabriella Bosco, Alan Pak Tao LauAbstract:In this paper, a simple novel digital Modulation Format identification (MFI) scheme for coherent optical systems is proposed. The scheme is based on the evaluation of the peak-to-average-power ratio (PAPR) of the incoming data samples after analog-to-digital conversion (ADC), chromatic dispersion (CD) and polarization mode demultiplexing (PMD) compensation at the receiver (Rx). Since at a particular optical-signal-to-noise ratio (OSNR) value different Modulation Formats have distinct PAPR values, it is possible to identify them. The proposed scheme and the results are analyzed both experimentally and through numerical simulations. The results demonstrate successful identification among four Modulation Formats (MF) commonly used in digital coherent systems.
-
automatic Modulation Format bit rate classification and signal to noise ratio estimation using asynchronous delay tap sampling
Computers & Electrical Engineering, 2015Co-Authors: Faisal Nadeem Khan, Yudi Zhou, Ming Chieng Tan, Waled Hussein Alarashi, Chiew Hoon Teow, Shiu Guong Kiu, Alan Pak Tao LauAbstract:A technique for joint Modulation Format and bit-rate classification is proposed.The proposed technique can simultaneously enable non-data-aided SNR estimation.The technique uses asynchronous delay-tap plots with artificial neural networks.The signal classification accuracy is 99.12% and mean SNR estimation error is 0.88?dB.Due to its simplicity, it is attractive for future cognitive wireless networks. We propose a novel technique for automatic classification of Modulation Formats/bit-rates of digitally modulated signals as well as non-data-aided (NDA) estimation of signal-to-noise ratio (SNR) in wireless networks. The proposed technique exploits Modulation Format, bit-rate, and SNR sensitive features of asynchronous delay-tap plots (ADTPs) for the joint estimation of these parameters. Simulation results validate successful classification of three commonly-used Modulation Formats at two different bit-rates with an overall accuracy of 99.12%. Similarly, in-service estimation of SNR in the range of 0-30 dB is demonstrated with mean estimation error of 0.88 dB. The proposed technique requires low-speed asynchronous sampling of signal envelope and hence, it can enable simple and cost-effective joint Modulation Format/bit-rate classification and NDA SNR estimation in future wireless networks. Display Omitted
Kangping Zhong - One of the best experts on this subject based on the ideXlab platform.
-
subtraction clustering based Modulation Format identification in stokes space
IEEE Photonics Technology Letters, 2017Co-Authors: Pengyu Chen, Jie Liu, Kangping Zhong, Xiaofeng MaiAbstract:A 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. Experimental verifications are also performed to prove the feasibility of the proposed MFI in long-distance optical fiber transmission systems.
-
joint osnr monitoring and Modulation Format identification in digital coherent receivers using deep neural networks
Optics Express, 2017Co-Authors: Faisal Nadeem Khan, Kangping Zhong, Xian Zhou, Waled Hussein Alarashi, Alan Pak Tao LauAbstract:We experimentally demonstrate the use of deep neural networks (DNNs) in combination with signals’ amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio (OSNR) monitoring and Modulation Format identification (MFI) in digital coherent receivers. The proposed technique automatically extracts OSNR and Modulation Format dependent features of AHs, obtained after constant modulus algorithm (CMA) equalization, and exploits them for the joint estimation of these parameters. Experimental results for 112 Gbps polarization-multiplexed (PM) quadrature phase-shift keying (QPSK), 112 Gbps PM 16 quadrature amplitude Modulation (16-QAM), and 240 Gbps PM 64-QAM signals demonstrate OSNR monitoring with mean estimation errors of 1.2 dB, 0.4 dB, and 1 dB, respectively. Similarly, the results for MFI show 100% identification accuracy for all three Modulation Formats. The proposed technique applies deep machine learning algorithms inside standard digital coherent receiver and does not require any additional hardware. Therefore, it is attractive for cost-effective multi-parameter estimation in next-generation elastic optical networks (EONs).
-
joint osnr monitoring and Modulation Format identification in digital coherent receivers using deep neural networks
Optics Express, 2017Co-Authors: Faisal Nadeem Khan, Kangping Zhong, Xian Zhou, Waled Hussein Alarashi, Changyuan Yu, Chao LuAbstract:We experimentally demonstrate the use of deep neural networks (DNNs) in combination with signals’ amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio (OSNR) monitoring and Modulation Format identification (MFI) in digital coherent receivers. The proposed technique automatically extracts OSNR and Modulation Format dependent features of AHs, obtained after constant modulus algorithm (CMA) equalization, and exploits them for the joint estimation of these parameters. Experimental results for 112 Gbps polarization-multiplexed (PM) quadrature phase-shift keying (QPSK), 112 Gbps PM 16 quadrature amplitude Modulation (16-QAM), and 240 Gbps PM 64-QAM signals demonstrate OSNR monitoring with mean estimation errors of 1.2 dB, 0.4 dB, and 1 dB, respectively. Similarly, the results for MFI show 100% identification accuracy for all three Modulation Formats. The proposed technique applies deep machine learning algorithms inside standard digital coherent receiver and does not require any additional hardware. Therefore, it is attractive for cost-effective multi-parameter estimation in next-generation elastic optical networks (EONs).
-
signal power distribution based Modulation Format identification for coherent optical receivers
Optical Fiber Technology, 2017Co-Authors: Jie Liu, Changjian Guo, Kangping Zhong, Zhenhua Dong, Alan Pak Tao LauAbstract:Abstract A simple Modulation Format identification (MFI) technique based on extracting features from the statistical distributions of normalized signal power is proposed for cognitive coherent optical receivers. The proposed MFI technique requires no prior training and is independent of phase noise or frequency offset. Furthermore, it also performs good identification of the polarization-multiplexed (PM) M-QAM signals even after insufficient equalization of the constant modulus algorithm (CMA). Simulation results demonstrate successful MFI among PM-QPSK, PM-8-QAM, PM-16-QAM, PM-32-QAM and PM-64-QAM signals within OSNR range of practical system. Experimental verification using PM-QPSK/16-QAM/64-QAM signals also confirms the feasibility of the proposed MFI technique after long distance fiber transmission.
-
Modulation Format identification in coherent receivers using deep machine learning
IEEE Photonics Technology Letters, 2016Co-Authors: Faisal Nadeem Khan, Kangping Zhong, Waled Hussein Alarashi, Alan Pak Tao LauAbstract:We 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. Experimental results for three commonly-used Modulation Formats demonstrate MFI with an accuracy of 100% over a wide optical signal-to-noise ratio (OSNR) range. The effects of fiber nonlinearity on the performance of MFI technique are also investigated. The proposed technique is non-data-aided (NDA) and avoids any additional hardware on top of standard digital coherent receiver. Therefore, it is ideal for simple and cost-effective MFI in future heterogeneous optical networks.
Akihiro Maruta - One of the best experts on this subject based on the ideXlab platform.
-
all optical pam4 to 16qam Modulation Format conversion using nonlinear optical loop mirror and 1 2 coupler
International Conference on Photonics in Switching, 2019Co-Authors: Yuta Matsumoto, Ken Mishina, Daisuke Hisano, Akihiro MarutaAbstract:We propose an all-optical PAM4 to 16QAM Modulation Format conversion using NOLM The successful operation of the conversion from 2 × 25-Gbaud PAM4 signals to 100-Gbps 16QAM signal is confirmed by numerical simulation.
-
All-optical NRZ-OOK/RZ-BPSK Modulation Format conversion for wavelength multicasting based on cross-phase Modulation in optical fiber
2012Co-Authors: Nana Horaguchi, Akihiro Tokunaga, Akihiro MarutaAbstract:We propose wavelength multicasting scheme accompanied with NRZ-OOK/RZ-BPSK Modulation Format conversion based on cross-phase Modulation in optical fiber. We experimentally demonstrate error-free operation from 10.7 Gb/s NRZ-OOK signal to four channels 10.7 Gb/s RZ-BPSK signals.
-
design of all optical nrz ook rz qpsk Modulation Format converter by use of cross phase Modulation in optical fiber
Opto-Electronics and Communications Conference, 2012Co-Authors: Hiroki Terauchi, Akihiro Tokunaga, Nana Horaguchi, Akihiro MarutaAbstract:We describe a design method of all-optical NRZ-OOK/RZ-QPSK Modulation Format converter by use of cross phase Modulation in optical fiber. We experimentally show the validity of the design method.
-
all optical ook to 16 qam Modulation Format conversion employing nonlinear optical loop mirror
Journal of Lightwave Technology, 2012Co-Authors: Guoxiu Huang, Yuji Miyoshi, Yuki Yoshida, Akihiro Maruta, Ken-ichi KitayamaAbstract:This paper proposes and numerically demonstrates an all-optical on-off keying (OOK) to 16 quadrature amplitude Modulation (QAM) Format conversion using nonlinear optical loop mirror (NOLM) based on cross-phase Modulation (XPM) and parametric amplification in optical fibers. The 16-QAM signal is generated by the superposition of two quadrature phase shift keying (QPSK) signals with different amplitudes. OOK to QPSK Modulation Format conversion is achieved by XPM in one highly nonlinear fiber (HNLF). The amplitude ratio 2:1 of two QPSK signals can be realized by parametric amplification. The feasibility of OOK to 16-QAM Modulation Format conversion is confirmed at the symbol rate of 10 Gs/s by numerical simulation with the length of 27 - 1 pseudo random binary sequence (PRBS) input OOK signals. The tolerance of power deviation of the converter is also analytically evaluated.
-
all optical ook to 16qam Modulation Format conversion employing nonlinear optical fiber loop mirror
Optical Fiber Communication Conference, 2011Co-Authors: Guoxiu Huang, Yuji Miyoshi, Yuki Yoshida, Akihiro Maruta, Ken-ichi KitayamaAbstract:We propose a novel all-optical Modulation Format conversion scheme from on-off-keying to 16 quadrature amplitude Modulation using nonlinear optical loop mirror based on parametric amplification and cross-phase Modulation in optical fibers.
Christophe Peucheret - One of the best experts on this subject based on the ideXlab platform.
-
simultaneous qpsk to 2 times bpsk wavelength and Modulation Format conversion in ppln
IEEE Photonics Technology Letters, 2014Co-Authors: Francesco Da Ros, Kjeld Dalgaard, Yutaka Fukuchi, Michael Galili, Christophe PeucheretAbstract:Phase-sensitive cascaded second-harmonic generation and difference-frequency generation in a periodically poled lithium niobate waveguide allow converting two orthogonal quadratures of an optical field to different wavelengths, thus enabling simultaneous quadrature phase-shift keying-to- \(2\times \) binary phase-shift keying Modulation Format and wavelength conversions. Static phase-sensitive extinction ratios above 20 dB are obtained for both quadratures, resulting in error-free dynamic operation with low penalty (BER \(10^{-9}\) ) at 10 Gbaud.
-
Simultaneous QPSK-to-2×BPSK wavelength and Modulation Format conversion in PPLN
IEEE Photonics Technology Letters, 2014Co-Authors: Francesco Da Ros, Kjeld Dalgaard, Yutaka Fukuchi, Michael Galili, Christophe PeucheretAbstract:Phase-sensitive cascaded second-harmonic generation and difference-frequency generation in a periodically poled lithium niobate waveguide allow converting two orthogonal quadratures of an optical field to different wavelengths, thus enabling simultaneous quadrature phase-shift keying-to- 2×binary phase-shift keying Modulation Format and wavelength conversions. Static phase-sensitive extinction ratios above 20 dB are obtained for both quadratures, resulting in error-free dynamic operation with low penalty (BER 1e−9) at 10 Gbaud.
-
optical label swapping and packet transmission based on ask dpsk orthogonal Modulation Format in ip over wdm networks
Optical Fiber Communication Conference, 2003Co-Authors: Nan Chi, Lotte Jin Christiansen, Kresten Yvind, Jianfeng Zhang, Christophe Peucheret, C. Zhang, P V Holmnielsen, P. JeppesenAbstract:We demonstrate all-optical label swapping based on SOA, EAM and HNLF for a two-level optically labeled packet using orthogonal ASK/DPSK Modulation Format. The ASK/DPSK packet is successfully transmitted over 80 km NZDSF.
-
Optical label swapping and packet transmission based on ASK/DPSK orthogonal Modulation Format in IP-over-WDM networks
OFC 2003 Optical Fiber Communications Conference 2003., 2003Co-Authors: Nan Chi, Lotte Jin Christiansen, Kresten Yvind, Jianfeng Zhang, P.v. Holm-nielsen, Christophe Peucheret, C. Zhang, P. JeppesenAbstract:We demonstrate all-optical label swapping based on SOA, EAM and HNLF for a two-level optically labeled packet using orthogonal ASK/DPSK Modulation Format. The ASK/DPSK packet is successfully transmitted over 80 km NZDSF.
Idelfonso Tafur Monroy - One of the best experts on this subject based on the ideXlab platform.
-
Clustering algorithms for Stokes space Modulation Format recognition.
Optics express, 2015Co-Authors: Ricard Boada, Robert Borkowski, Idelfonso Tafur MonroyAbstract:Stokes space Modulation Format recognition (Stokes MFR) is a blind method enabling digital coherent receivers to infer Modulation Format inFormation directly from a received polarization-division-multiplexed signal. A crucial part of the Stokes MFR is a clustering algorithm, which largely influences the performance of the detection process, particularly at low signal-to-noise ratios. This paper reports on an extensive study of six different clustering algorithms: k-means, expectation maximization, density-based DBSCAN and OPTICS, spectral clustering and maximum likelihood clustering, used for discriminating between dual polarization: BPSK, QPSK, 8-PSK, 8-QAM, and 16-QAM. We determine essential performance metrics for each clustering algorithm and Modulation Format under test: minimum required signal-to-noise ratio, detection accuracy and algorithm complexity.
-
stokes space based optical Modulation Format recognition for digital coherent receivers
IEEE Photonics Technology Letters, 2013Co-Authors: Robert Borkowski, Darko Zibar, Antonio Caballero, Valeria Arlunno, Idelfonso Tafur MonroyAbstract:We present a technique for Modulation Format recognition for heterogeneous reconfigurable optical networks. The method is based on Stokes space signal representation and uses a variational Bayesian expectation maximization machine learning algorithm. Differentiation between diverse common coherent Modulation Formats is successfully demonstrated numerically and experimentally. The proposed method does not require training or a constellation diagram to operate, is insensitive to polarization mixing or frequency offset and can be implemented in any receiver capable of measuring Stokes parameters.
-
Optical Modulation Format recognition in stokes space for digital coherent receivers
Optical Fiber Communication Conference National Fiber Optic Engineers Conference 2013, 2013Co-Authors: Robert Borkowski, Darko Zibar, Antonio Caballero, Valeria Arlunno, Idelfonso Tafur MonroyAbstract:We report on a novel method for optical Modulation Format recognition based on Stokes parameters and variational expectation maximization algorithm. Discrimination among six different pol-muxed coherent Modulation Formats is successfully demonstrated in simulation and experiment.