2020
DOI: 10.1364/jocn.382267
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Modeling and mitigation of fiber nonlinearity in wideband optical signal transmission [Invited]

Abstract: The adoption of open optical networks (OONs) requires the development of open and effective network planning tools, enabling the use of multi-vendor or white box transport solutions. Such tools for studying and planning optical networks must be able to take into account the physical layer impairments, including fiber nonlinearity. The use of wideband wavelength division multiplexing in OONs, with channel frequencies extending across the short-, conventional-and long-bands (S, C and L-bands) and beyond, offers … Show more

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Cited by 41 publications
(26 citation statements)
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“…The NLI coefficient η n (f i ) experienced by the channel of frequency f i is calculated using the closed-form ISRS GN model proposed in [12]. This model is well suitable for modelling ultra-wideband transmission systems, and its accuracy compared to nonlinear Schrodinger equation (NLSE) simulations has been demonstrated at [12], [14].…”
Section: Transmission System Under Investigationmentioning
confidence: 99%
See 1 more Smart Citation
“…The NLI coefficient η n (f i ) experienced by the channel of frequency f i is calculated using the closed-form ISRS GN model proposed in [12]. This model is well suitable for modelling ultra-wideband transmission systems, and its accuracy compared to nonlinear Schrodinger equation (NLSE) simulations has been demonstrated at [12], [14].…”
Section: Transmission System Under Investigationmentioning
confidence: 99%
“…This creates to a N ch -dimensional optimisation problem. Additionally, in the presence of ISRS, this optimisation is non-convex, leading to multiple local solutions [14].…”
Section: Launch Power Optimisationmentioning
confidence: 99%
“…D. Dahan is also with the Department of Electrical Engineering, Holon Institute of Technology, 52 Golomb street, Holon 58102, Israel (email: david.dahan@huawei.com; michael.zarubinsky@huawei.com; liangyunhua1@huawei.com ) penalties as some portions of the channel optical power are transferred from higher to lower optical frequencies via nonlinear inelastic scattering of the signal photons by the fiber silica medium [8]. Accurate and reliable simulations of nonlinear DWDM systems with a large number of interfering channels (IC) are critical for designing and predicting the performance of fiber-communications systems [9][10][11], for the development of nonlinearity tolerant modulation formats and for devising effective nonlinearity equalization techniques [12][13][14], as well as for optical networking related applications such as optical channel monitoring [15], fast and accurate network planning tools [16] and means against physical layer related security threats [17]. Simulation of large channel-count systems are extremely demanding in terms of computational resources and often require unacceptably long computation time when relying on the conventional split-step Fourier-transform method (SSFTM) [18].…”
Section: Introductionmentioning
confidence: 99%
“…They include the Gaussian noise (GN) model [20], the enhanced Gaussian noise model (EGN) [21], both developed in the frequency domain and the time-varying intersymbol interference (ISI) model of the XPM induced NLIN [22][23]. Some of these models have also been extended to include the ISRS impact [11,24]. These models lead to semi-analytical solutions of the NLIN and in some contexts, they offer an acceptable alternative to SSFTM simulations.…”
Section: Introductionmentioning
confidence: 99%
“…It is particularly important to accurately and quickly evaluate the signal-to-noise ratio (SNR) of high-speed and ultra-wideband optical fiber communication systems. 1 The process of optical signal transmission in fiber is complex and unresolvable, but fortunately, the Enhanced GN-model (EGN model), [2][3][4][5][6][7][8][9][10][11] arising from the Gaussian noise perturbation analysis, can evaluate the system SNR accurately. To simplify the calculation, a closed-form formula is proposed using some mathematical approximation.…”
Section: Introductionmentioning
confidence: 99%