Scalable and Disaggregated GGN Approximation Applied to a C+L+S Optical Network

Abstract

We investigate quality of transmission (QoT) estimation in a multi-band transmission scenario, including a wideband description of the frequency-dependent physical layer parameters and a disaggregated QoT estimation approach.In particular, we use experimentally-derived erbium-and thulium-doped fiber amplifier operational data, and simulate the generation of the nonlinear interference (NLI) noise by comparing implementations of the split-step Fourier method, the generalized Gaussian noise (GGN) model implemented in the open-source GNPy library, and an efficient approximation that provides accurate results in a limited computational time. The latter semi-analytical solution is obtained by approaching the Manakov equation from a disaggregated standpoint, including the power transfer induced by stimulated Raman scattering, along with the frequency-dependent evolution of the fiber parameters of loss, dispersion and the nonlinearity coefficient. We validate the proposed approximation within a C+L+S 400 G transmission scenario and investigate 21 channels under test that are equally spaced along the three bands.

Multi-Band ESCL Transmission Supported by Bismuth-Doped and Raman Fiber Amplification

“…The most relevant parameters from a modeling perspective are: the fiber loss coefficient, α, the propagation constant, β, the nonlinear coefficient, γ, and the reference Raman gain coefficient, g 0 . More details about the origin and/or derivation of these parameters are given in [25].…”

“…To estimate the experimental QoT impairments, a semianalytical physical layer model that separately provides the linear and nonlinear contributors is presented, based on the methodology described in [25]. The QoT for a given CUT wavelength, λ, through a single fiber span is commonly quantified using the generalized signal-to-noise ratio (GSNR):…”

“…By approximating the SRS efficiency function, accurate closed-form solutions have been presented and verified in [42]- [44], however, this approximation becomes invalid when the CUT and interfering channel are separated by more than 13 THz, which corresponds to the peak of the SRS spectral efficiency. An alternative approach which is used in this work is to start with the generalized Gaussian noise (GGN) model and solve the Raman equations directly, in order to obtain the SRS efficiency function semi-analytically, as performed in [25].…”

“…The quantities η λ and η λκ emerge from the derivation of the PMD-Manakov equation [46], [47]. We direct readers seeking further detail about the derivation of these parameters to [25], as a full derivation is outside the scope of this work. As transmission is performed over a single span of fiber, typical issues which arise due to the coherent accumulation of the SC contributor are not present [45], meaning that the total NLI power of the WDM signal can be found by separately calculating the SC and XC impairments, for each CUT, producing a superposition of effects [48].…”

“…Beyond challenges in component development, more sophisticated models are needed to evaluate the quality of transmission (QoT) in MBT scenarios [25], [26]. Quantifying QoT is necessary to estimate the possible/achievable capacity increases when expanding the spectrum into new bands, and to evaluate the feasibility of current and future lightpaths (LPs).…”