Introduction to polarization mode dispersion in optical systems

Nelson, L.E.; Jopson, R.M.

doi:10.1007/s10297-004-0001-5

Cited by 21 publications

(6 citation statements)

References 78 publications

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“…Pairs for the birefringence correlation length and the birefringence beat length (L C , L B ) have been tested in the ranges of 0.5 m L C 10 m and 0.1 m L B 10 m, respectively. These ranges have been settled in order to include the set of values found typical for L C and L B in singlecore telecommunication fibers [37,41,42] (p. 6), [35] (pp. 251, 261, 267, 269).…”

Section: Brief Description About the Simulator Implementationmentioning

confidence: 99%

Correlation and Power Distribution of Intercore Crosstalk Field Components of Polarization-Coupled Weakly Coupled Single-Mode Multicore Fibres

Morgado

Cartaxo

2021

Photonics

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The correlation and power distribution of intercore crosstalk (ICXT) field components of weakly coupled multicore fibers (WC-MCFs) are important properties that determine the statistics of the ICXT and ultimately impact the performance of WC-MCF optical communication systems. Using intensive numerical simulation of the coupled mode equations describing ICXT of a single-mode WC-MCF with intracore birefringence and linear propagation, we assess the mean, correlation, and power distribution of the four ICXT field components of unmodulated polarization-coupled homogeneous and quasi-homogeneous WC-MCFs with a single interfering core in a wide range of birefringence conditions and power distribution among the field components at the interfering core input. It is shown that, for homogeneous and quasi-homogeneous WC-MCFs, zero mean uncorrelated ICXT field components with similar power levels are observed for birefringence correlation length and birefringence beat length in the ranges of 0.5m,10m and 0.1m,10m, respectively, regardless of the distribution of power between the four field components at the interfering core input.

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Section: Brief Description About the Simulator Implementationmentioning

confidence: 99%

Correlation and Power Distribution of Intercore Crosstalk Field Components of Polarization-Coupled Weakly Coupled Single-Mode Multicore Fibres

Morgado

Cartaxo

2021

Photonics

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“…The evolution of DP signals through a single-mode fiber can be described by a set of coupled NLSEs that takes into account the interactions between the two degenerate polarization modes as a function of propagation distance [21]. In birefringent fibers where the PSP changes rapidly along the link, propagation in a noiseless fiber is governed by the Manakov-PMD equation [32]…”

Section: A the Manakov-pmd Equationmentioning

confidence: 99%

“…For multi-layer models, it is important to simplify the individual steps as much as possible to limit the overall complexity [18], [19]. This is especially important since PMD is a time-varying impairment that requires adaptive filtering in practice [21]. We therefore propose to simplify the individual linear steps by decomposing the MIMO-FIR filter into three components as illustrated in the top part of Fig.…”

Section: Proposed Machine-learning Modelmentioning

confidence: 99%

“…The complexity of the MIMO filters is reduced by decomposing them into separate FIR filters for each polarization followed by memoryless rotation matrices [18], [19]. This decomposition mimics the forward propagation model, where PMD introduces a polarizationdependent differential group delay (DGD) and rotates the principal states of polarization (PSP) along the fiber link in a distributed fashion [21].…”

Section: Introductionmentioning

confidence: 99%

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Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

Bütler,

Häger,

Pfister

et al. 2020

Preprint

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In this paper, we propose a model-based machinelearning approach for dual-polarization systems by parameterizing the split-step Fourier method for the Manakov-PMD equation. The resulting method combines hardware-friendly timedomain nonlinearity mitigation via the recently proposed learned digital backpropagation (LDBP) with distributed compensation of polarization-mode dispersion (PMD). We refer to the resulting approach as LDBP-PMD. We train LDBP-PMD on multiple PMD realizations and show that it converges within 1% of its peak dB performance after 428 training iterations on average, yielding a peak effective signal-to-noise ratio of only 0.30 dB below the PMD-free case. Similar to state-of-the-art lumped PMD compensation algorithms in practical systems, our approach does not assume any knowledge about the particular PMD realization along the link, nor any knowledge about the total accumulated PMD. This is a significant improvement compared to prior work on distributed PMD compensation, where knowledge about the accumulated PMD is typically assumed. We also compare different parameterization choices in terms of performance, complexity, and convergence behavior. Lastly, we demonstrate that the learned models can be successfully retrained after an abrupt change of the PMD realization along the fiber.

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“…Polarization mode dispersion (PMD), caused by the birefringence of the optical fiber and the random variation of its orientation along the fiber length is the major source of noise in the DP‐PTS system. The PMD results in crosstalk between the two polarization channels while propagating through the second spool of DCF.…”

Section: Spectral Efficiency Improvement In Tsadc Via Polarization Mumentioning

confidence: 99%

Photonic time‐stretch digitizer and its extension to real‐time spectroscopy and imaging

Fard

Gupta

Jalali

2013

Laser & Photonics Reviews

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Real-time wideband digitizers are the key building block in many systems including oscilloscopes, signal intelligence, electronic warfare, and medical diagnostics systems. Continually extending the bandwidth of digitizers has hence become a central challenge in electronics. Fortunately, it has been shown that photonic pre-processing of wideband signals can boost the performance of electronic digitizers. In this article, the underlying principle of the time-stretch analog-to-digital converter (TSADC) that addresses the demands on resolution, bandwidth, and spectral efficiency is reviewed. In the TSADC, amplified dispersive Fourier transform is used to slow down the analog signal in time and hence to compress its bandwidth. Simultaneous signal amplification during the time-stretch process compensates for parasitic losses leading to high signal-to-noise ratio. This powerful concept transforms the analog signal's time scale such that it matches the slower time scale of the digitizer. A summary of time-stretch technology's extension to highthroughput single-shot spectroscopy, a technique that led to the discovery of optical rouge waves, is also presented. Moreover, its application in high-throughput imaging, which has recently led to identification of rogue cancer cells in blood with record sensitivity, is discussed.

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Introduction to polarization mode dispersion in optical systems

Cited by 21 publications

References 78 publications

Correlation and Power Distribution of Intercore Crosstalk Field Components of Polarization-Coupled Weakly Coupled Single-Mode Multicore Fibres

Correlation and Power Distribution of Intercore Crosstalk Field Components of Polarization-Coupled Weakly Coupled Single-Mode Multicore Fibres

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

Photonic time‐stretch digitizer and its extension to real‐time spectroscopy and imaging

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