Advanced DSP Techniques Enabling High Spectral Efficiency and Flexible Transmissions: Toward elastic optical networks

Lau, Alan Pak Tao; Gao, Yuliang; Shu, Qi; Wang, Dawei; Zhuge, Qunbi; Morsy-Osman, Mohamed; Chagnon, Mathieu; Xu, Xia; Lu, Chao; Plant, David V.

doi:10.1109/msp.2013.2287021

Cited by 56 publications

(15 citation statements)

References 26 publications

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“…The uncertainty associated with the prediction is given by the apriori error covariance matrix P k|k-1 , as in Eq. (5). Under the given assumptions and initial conditions, the conditional probability density function (pdf) p(x k |y 1 ,y 2 ,…,y k-1 ) is also Gaussian, where the apriori state estimatex kjkÀ1 and the apriori error covariance P k|k-1 , reflects the mean and variance of the distribution, as given in Eq.…”

Section: Principles Of Kalman Filtermentioning

confidence: 99%

“…In order to meet the yearning demands of bandwidth and capacity due to ever increasing data traffic, the contemporary research in the field of optical transmission, is focused on developing 400 Gbps and above, Ethernet transmission [1][2][3][4][5]. The achievable information rates using optical fiber as communication channel have been rapidly increased over the past few decades.…”

Section: Introductionmentioning

confidence: 99%

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Applications of Kalman Filters for Coherent Optical Communication Systems

Pakala¹,

Schmauß²

2018

Kalman Filters - Theory for Advanced Applications

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In this chapter, we review various applications of Kalman filtering for coherent optical communication systems. First, we briefly discuss the principles of Kalman filter and its variations including extended Kalman filter (EKF) and adaptive Kalman filter (AKF). Later on, we illustrate the applicability of Kalman filters for joint tracking of several optical transmission impairments, simultaneously, by formulating the state space model (SSM) and detailing the principles. A detailed methodology is presented for the joint tracking of linear and nonlinear phase noise along with amplitude noise using EKF. Also, approaches to enhance the performance obtained by EKF by combining with other existing digital signal processing (DSP) techniques are presented. Frequency and phase offset estimation using a two stage linear Kalman filter (LKF)/EKF is also discussed. A cascaded structure of LKF and EKF by splitting the SSM to jointly mitigate the effects of polarization, phase and amplitude noise is also presented. The numerical analysis concludes that the Kalman filter based approaches outperform the conventional methods with better tracking capability and faster convergence besides offering more feasibility for real-time implementations.

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Section: Principles Of Kalman Filtermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applications of Kalman Filters for Coherent Optical Communication Systems

Pakala¹,

Schmauß²

2018

Kalman Filters - Theory for Advanced Applications

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“…At the receiver side, the reverse operations are performed using a coherent receiver. First, the symbol clock, carrier phase, and polarization are recovered using either blind or pilot-aided estimation algorithms [15][16][17]. A balanced detector now outputs the N received baseband waveforms, represented by the vector y(t), which should hopefully resemble x(t).…”

Section: System Modelsmentioning

confidence: 99%

“…The parameters of the (255,239) RS code, converted from bytes to bits, are (n, k, d H ) = (2040,1912,17). This code can, if combined with BPSK modulation as in (2.17), be regarded as a 2040-dimensional constellation with parameters β = 1.87, CFM = 15.31 dB, γ = 12.02 dB, and G = 11.79 dB.…”

Section: Soft-decision Decodingmentioning

confidence: 99%

Multidimensional Optimized Optical Modulation Formats

Karlsson

Agrell

2016

Enabling Technologies for High Spectral‐Efficiency Coherent Optical Communication Networks

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Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published source. Please note that access to the published version might require a subscription. Chalmers Publication Library (CPL) offers the possibility of retrieving research publications produced at Chalmers University of Technology. It covers all types of publications: articles, dissertations, licentiate theses, masters theses, conference papers, reports etc. Since 2006 it is the official tool for Chalmers official publication statistics. To ensure that Chalmers research results are disseminated as widely as possible, an Open Access Policy has been adopted. The CPL service is administrated and maintained by Chalmers Library.

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“…In order to achieve higher spectral efficiency [1] and better quality of service, flexible and programmable optical networks are needed. Thus, the elastic optical network (EON) [2] with the capability to adaptively adjust the data rate, bandwidth, modulation format and signal power according to variable traffic demand has attracted extensive attention in recent years [3]. For EON, the information about the physical state of transmission link and the quality of optical signals should be available.…”

Section: Introductionmentioning

confidence: 99%

OSNR Monitoring Using Support Vector Ordinal Regression for Digital Coherent Receivers

Hao

Yan

et al. 2019

IEEE Photonics J.

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An OSNR monitoring method assisted by support vector ordinal regression (SVOR) is proposed for digital coherent receivers. According to Godard's error of equalized signals obtained after polarization demultiplexing, the optical signal-to-noise ratio (OSNR) value could be effectively estimated by using SVOR. The effectiveness of the proposed OSNR monitoring method is verified via numerical simulations with 28-Gbaud PDM-QPSK, PDM-8PSK, PDM-8QAM, PDM-16QAM and PDM-32QAM signals. The simulation results show that the 100% accuracies for the five modulation formats can be obtained over a wide OSNR range. The feasibility is further demonstrated by proof-of-concept experiments in 28-Gbaud PDM-QPSK, PDM-8PSK, PDM-8QAM and PDM-16QAM systems. The errors of averaged values of estimated OSNR for all the signals are less than or equal to 0.2 dB.

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Advanced DSP Techniques Enabling High Spectral Efficiency and Flexible Transmissions: Toward elastic optical networks

Cited by 56 publications

References 26 publications

Applications of Kalman Filters for Coherent Optical Communication Systems

Applications of Kalman Filters for Coherent Optical Communication Systems

Multidimensional Optimized Optical Modulation Formats

OSNR Monitoring Using Support Vector Ordinal Regression for Digital Coherent Receivers

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