51 research outputs found
On the Impact of Optimal Modulation and FEC Overhead on Future Optical Networks
The potential of optimum selection of modulation and forward error correction
(FEC) overhead (OH) in future transparent nonlinear optical mesh networks is
studied from an information theory perspective. Different network topologies
are studied as well as both ideal soft-decision (SD) and hard-decision (HD) FEC
based on demap-and-decode (bit-wise) receivers. When compared to the de-facto
QPSK with 7% OH, our results show large gains in network throughput. When
compared to SD-FEC, HD-FEC is shown to cause network throughput losses of 12%,
15%, and 20% for a country, continental, and global network topology,
respectively. Furthermore, it is shown that most of the theoretically possible
gains can be achieved by using one modulation format and only two OHs. This is
in contrast to the infinite number of OHs required in the ideal case. The
obtained optimal OHs are between 5% and 80%, which highlights the potential
advantage of using FEC with high OHs.Comment: Some minor typos were correcte
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Approximating the Partially Coherent Additive White Gaussian Noise Channel in Polar Coordinates
We consider the partially coherent additive white
Gaussian noise channel (PCAWGN) in optical communications
and review the derivation of the exact channel conditional
probability model in a closed-form solution in polar coordinates.
In addition, we derive a reduced-complexity approximation
by replacing the Rician and Tikhonov distributions describing amplitude and phase components, respectively, with their
Gaussian approximation under certain assumptions of high
SNR and low phase noise or jitter. Our proposal significantly
reduces the hardware complexity by removing the modified
Bessel functions involved in the exact solution. Furthermore,
we compare the proposed approximation with a different metric
previously found in the literature and observe that for maximumlikelihood hard symbol decision, both models are in perfect
agreement with the optimal detector. However, our model not only
reduces the required number of multiplications from 12 to 8 and
additions from 9 to 3 (per computed symbol) but also reduces
the information loss by at least one and up to several orders of
magnitude with respect to the previously published metric when
used to compute the channel achievable information rate (AIR).
In all the simulation cases, we use QAM constellations of orders
4, 8, 16, and 32 as test input symbol sets
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Machine Learning based Noise Estimation in Optical Fiber Communication Networks
In this paper, we discuss a machine learning based approach to jointly estimating both linear and nonlinear noise contributions in an optical fiber communication link. We will expound the rational for utilizing machine learning for this problem, before discussing current progress and then concluding with future research directions.The authors gratefully acknowledge the donation of equipment, funding and support from Ciena. This research was performed under the auspices of a Ciena university collaborative research grant. S. J. Savory also acknowledges support from UK EPSRC (through the project INSIGHT EP/L026155/2)
Why compensating fibre nonlinearity will never meet capacity demands
Current research efforts are focussed on overcoming the apparent limits of
communication in single mode optical fibre resulting from distortion due to
fibre nonlinearity. It has been experimentally demonstrated that this Kerr
nonlinearity limit is not a fundamental limit; thus it is pertinent to review
where the fundamental limits of optical communications lie, and direct future
research on this basis. This paper details recently presented results. The work
herein briefly reviews the intrinsic limits of optical communication over
standard single mode optical fibre (SMF), and shows that the empirical limits
of silica fibre power handling and transceiver design both introduce a
practical upper bound to the capacity of communication using SMF, on the order
of 1 Pbit/s. Transmission rates exceeding 1 Pbit/s are shown to be possible,
however, with currently available optical fibres, attempts to transmit beyond
this rate by simply increasing optical power will lead to an asymptotically
zero fractional increase in capacity.Comment: 4 pages, 2 figure
Data-Driven Erbium-doped Fiber Amplifier Gain Modeling Using Gaussian Process Regression
We propose a data-driven erbium-doped fiber amplifier (EDFA) gain model utilizing Gaussian process regression (GPR). An additive Laplacian and radial-basis function kernel is proposed for the GPR and was found to outperform deep neural network (DNN) methods while additionally providing prediction uncertainty. Performance is measured using mean absolute error (MAE) averaged across five different EDFAs with three manufacturers. The GPR achieves an MAE of 0.1 dB using 30 training samples in contrast to the DNN that achieves an MAE of 0.25 dB using 3000 training samples. Additionally, we demonstrate that active learning can be used to improverobustness and repeatability of convergence
Maximizing the information throughput of ultra-wideband fiber-optic communication systems
Maximized information rates of ultra-wideband (typically, beyond 100~nm modulated bandwidth) lumped-amplified fiber-optic communication systems have been thoroughly examined accounting for the wavelength dependencies of optical fiber parameters in conjunction with the impact of the inelastic inter-channel stimulated Raman scattering (SRS). Three strategies to maximize point-to-point link throughput were proposed: optimizations of non-uniformly and uniformly distributed launch power per channel and the optimization based on adjusting to the target 3 dB ratio between the power of linear amplified spontaneous emission and nonlinear interference noise. The results clearly emphasize the possibility to approach nearly optimal system performance by means of implementing pragmatic engineering sub-optimal optimization strategies
200 Gb/s/ λ Bidirectional Coherent PON Solutions Demonstrated over Field Installed Fiber
We demonstrate 200 Gb/s bidirectional coherent PON solutions using a simplified optical network unit (ONU) over 19 km of field-installed fiber. The ONU receiver is a single-polarization heterodyne detector with either a balanced or a single-ended photodetector and the transmitter is based on dual-polarization electro-absorption modulated laser (EML). The optical line terminal (OLT) uses standard dual-polarization coherent transceivers. The downstream solutions achieve 37 dB and 30.5 dB power budget for the receiver with balanced and single-ended photodiodes, respectively. For the upstream, two line rates have been investigated: 200 Gb/s/λ for symmetrical transmission and 100 Gb/s/λ for asymmetric transmission achieving a power budget of 30.1 dB and 40.9 dB respectively
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