Experimental characterization of Gaussian-distributed nonlinear distortions

Vacondio, F.; Simonneau, C.; Lorcy, L.; Antona, Jean‐Christophe; Bononi, A.; Bigo, S.

doi:10.1364/ecoc.2011.we.7.b.1

Cited by 24 publications

(13 citation statements)

References 4 publications

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“…However, it has been shown that systems without inline dispersion compensation offer performance advantages over dispersion-managed systems [29]. This arises from the fact that [29][30][31][32][33] uncompensated dispersion renders the four signal components-X, Y, I, and Q-statistically independent, noise-like, and Gaussian-distributed at reception. This Gaussian characteristic is also maintained throughout the DSP chain.…”

Section: Gaussian Noise Model Of Nonlinear Link Noisementioning

confidence: 99%

Advanced signaling technologies for high-speed digital fiber-optic links

et al. 2014

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We summarize the most recent research of the Georgia Tech Terabit Optical Networking Consortium and the state-of-the-art in fiber telecommunications. These results comprise high-capacity single-mode fiber systems with digital coherent receivers and shorter-reach multimode fiber links with vertical cavity surface emitting lasers. We strongly emphasize the capabilities that sophisticated digital signal processing and electronics add to these fiber-based data transport links.

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Section: Gaussian Noise Model Of Nonlinear Link Noisementioning

confidence: 99%

Advanced signaling technologies for high-speed digital fiber-optic links

et al. 2014

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“…is the ASE power from both polarizations, where N is the number of spans and β = hνF(G − 1) depends on the in-line amplifiers noise figure F and gain G = e αz A , being α the fiber loss coefficient and z A the span length; N NL = E[|n n n NL | 2 ] = a NL P 3 is the NLI power obtained from a first-order regular perturbation [3,5]. The final relationship between Q-factor and SNR then depends on the modulation format [5,6,8]. The main goal of this paper is to provide an approximate analytical expression of the NLI coefficient a NL , valid for dominant IFWM, in any DM or NDM link.…”

Section: Nonlinear Gaussian Modelmentioning

confidence: 99%

“…It has recently been shown that, in high bit-rate coherent optical links with no dispersion management (NDM), the nonlinear interference (NLI) is a zero-mean signal-independent additive circular complex-Gaussian noise already after a few spans [1,2]. Based on such a key observation, a nonlinear Gaussian model for NDM coherent communications has been proposed [3][4][5] and experimentally validated [6][7][8]. In wavelength division multiplexing (WDM), the nonlinear noise comes both from intrachannel nonlinearity and from interchannel nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Modeling nonlinearity in coherent transmissions with dominant intrachannel-four-wave-mixing

Bononi¹,

Serena²,

Rossi³

et al. 2012

Opt. Express

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By extending a well-established time-domain perturbation approach to dual-polarization propagation, we provide an analytical framework to predict the nonlinear interference (NLI) variance, i.e., the variance induced by nonlinearity on the sampled field, and the nonlinear threshold (NLT) in coherent transmissions with dominant intrachannel-four-wave-mixing (IFWM). Such a framework applies to non dispersion managed (NDM) very long-haul coherent optical systems at nowadays typical baudrates of tens of Gigabaud, as well as to dispersion-managed (DM) systems at even higher baudrates, whenever IFWM is not removed by nonlinear equalization and is thus the dominant nonlinearity. The NLI variance formula has two fitting parameters which can be calibrated from simulations. From the NLI variance formula, analytical expressions of the NLT for both DM and NDM systems are derived and checked against recent NLT Monte-Carlo simulations.

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“…This nonlinear noise can be described as a Gaussian noise [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19], at least in dispersion uncompensated (DU) coherent systems. Gaussian nature of the nonlinear interference (NLI) noise fields is conditioned by Gaussian distribution of the information sampled signal [4][5][6][14][15][16].…”

Section: Introductionmentioning

confidence: 99%