Spatial-division multiplexing (SDM) and band-division multiplexing
(BDM) have emerged as solutions to expand the capacity of existing
C-band wavelength-division multiplexing (WDM) optical systems and to
deal with increasing traffic demands. An important difference between
these two approaches is that BDM solutions enable data transmission
over unused spectral bands of already-deployed optical fibers, whereas
SDM solutions require the availability of additional fibers to
replicate C-band WDM transmission. On the other hand, to properly
design a multiband optical line system (OLS), the following fiber
propagation effects have been taken into account in the analysis:
(i) stimulated Raman scattering (SRS), which induces considerable
power transfer among bands; (ii) frequency dependence of fiber
parameters such as attenuation, dispersion, and nonlinear
coefficients; and (iii) utilization of optical amplifiers with
different doping materials, thus leading to different characteristics,
e.g., in terms of noise figures. This work follows a two-step
approach: First, we aim at maximizing and flattening the quality of
transmission (QoT) when adding L- and
-bands to a traditional WDM OLS where
only the C-band is deployed. This is achieved by
applying a multiband optimized optical power control for BDM upgrades,
which consists of setting a pre-tilt and power offset in the line
amplifiers, thus achieving a considerable increase in QoT, both in
average value and flatness. Second, the SDM approach is used as a
benchmark for the BDM approach by assessing network performance on
three network topologies with different geographical footprints. We
show that, with optical power properly optimized, BDM may enable an
increase in network traffic, slightly less than an SDM upgrade but
still comparable, without requiring additional fiber cables.
We investigate on the network capacity enabled by C+L optical line systems (OLS) vs. fiber doubling showing that at optimal power, C+L OLS doubles the traffic of C-only with very-low penalty with respect to fiber doubling.
The reduction of system margin in open optical line systems (OLSs) requires the capability to predict the quality of transmission (QoT) within them. This quantity is given by the generalized signal-to-noise ratio (GSNR), including both the effects of amplified spontaneous emission (ASE) noise and nonlinear interference accumulation. Among these, estimating the ASE noise is the most challenging task due to the spectrally resolved working point of the erbium-doped fiber amplifiers (EDFAs), which depend on the spectral load, given the overall gain profile. An accurate GSNR estimation enables control of the power optimization and the possibility to automatically deploy lightpaths with a minimum margin in a reliable manner. We suppose an agnostic operation of the OLS, meaning that the EDFAs are operated as black boxes and rely only on telemetry data from the optical channel monitor at the end of the OLS. We acquire an experimental data set from an OLS made of 11 EDFAs and show that, without any knowledge of the system characteristics, an average extra margin of 2.28 dB is necessary to maintain a conservative threshold of QoT. Following this, we applied deep neural network machine-learning techniques, demonstrating a reduction in the needed margin average down to 0.15 dB.
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