15,153 research outputs found
A survey on fiber nonlinearity compensation for 400 Gbps and beyond optical communication systems
Optical communication systems represent the backbone of modern communication
networks. Since their deployment, different fiber technologies have been used
to deal with optical fiber impairments such as dispersion-shifted fibers and
dispersion-compensation fibers. In recent years, thanks to the introduction of
coherent detection based systems, fiber impairments can be mitigated using
digital signal processing (DSP) algorithms. Coherent systems are used in the
current 100 Gbps wavelength-division multiplexing (WDM) standard technology.
They allow the increase of spectral efficiency by using multi-level modulation
formats, and are combined with DSP techniques to combat the linear fiber
distortions. In addition to linear impairments, the next generation 400 Gbps/1
Tbps WDM systems are also more affected by the fiber nonlinearity due to the
Kerr effect. At high input power, the fiber nonlinear effects become more
important and their compensation is required to improve the transmission
performance. Several approaches have been proposed to deal with the fiber
nonlinearity. In this paper, after a brief description of the Kerr-induced
nonlinear effects, a survey on the fiber nonlinearity compensation (NLC)
techniques is provided. We focus on the well-known NLC techniques and discuss
their performance, as well as their implementation and complexity. An extension
of the inter-subcarrier nonlinear interference canceler approach is also
proposed. A performance evaluation of the well-known NLC techniques and the
proposed approach is provided in the context of Nyquist and super-Nyquist
superchannel systems.Comment: Accepted in the IEEE Communications Surveys and Tutorial
Machine learning for fiber nonlinearity mitigation in long-haul coherent optical transmission systems
Fiber nonlinearities from Kerr effect are considered as major constraints for enhancing the transmission capacity in current optical transmission systems. Digital nonlinearity compensation techniques such as digital backpropagation can perform well but require high computing resources. Machine learning can provide a low complexity capability especially for high-dimensional classification problems. Recently several supervised and unsupervised machine learning techniques have been investigated in the field of fiber nonlinearity mitigation. This paper offers a brief review of the principles, performance and complexity of these machine learning approaches in the application of nonlinearity mitigation
Integrated Transversal Equalizers in High-Speed Fiber-Optic Systems
Intersymbol interference (ISI) caused by intermodal dispersion in multimode fibers is the major limiting factor in the achievable data rate or transmission distance in high-speed multimode fiber-optic links for local area networks applications. Compared with optical-domain and other electrical-domain dispersion compensation methods, equalization with transversal filters based on distributed circuit techniques presents a cost-effective and low-power solution. The design of integrated distributed transversal equalizers is described in detail with focus on delay lines and gain stages. This seven-tap distributed transversal equalizer prototype has been implemented in a commercial 0.18-µm SiGe BiCMOS process for 10-Gb/s multimode fiber-optic links. A seven-tap distributed transversal equalizer reduces the ISI of a 10-Gb/s signal after 800 m of 50-µm multimode fiber from 5 to 1.38 dB, and improves the bit-error rate from about 10^-5 to less than 10^-12
Nonlinearity Mitigation in WDM Systems: Models, Strategies, and Achievable Rates
After reviewing models and mitigation strategies for interchannel nonlinear
interference (NLI), we focus on the frequency-resolved logarithmic perturbation
model to study the coherence properties of NLI. Based on this study, we devise
an NLI mitigation strategy which exploits the synergic effect of phase and
polarization noise compensation (PPN) and subcarrier multiplexing with
symbol-rate optimization. This synergy persists even for high-order modulation
alphabets and Gaussian symbols. A particle method for the computation of the
resulting achievable information rate and spectral efficiency (SE) is presented
and employed to lower-bound the channel capacity. The dependence of the SE on
the link length, amplifier spacing, and presence or absence of inline
dispersion compensation is studied. Single-polarization and dual-polarization
scenarios with either independent or joint processing of the two polarizations
are considered. Numerical results show that, in links with ideal distributed
amplification, an SE gain of about 1 bit/s/Hz/polarization can be obtained (or,
in alternative, the system reach can be doubled at a given SE) with respect to
single-carrier systems without PPN mitigation. The gain is lower with lumped
amplification, increases with the number of spans, decreases with the span
length, and is further reduced by in-line dispersion compensation. For
instance, considering a dispersion-unmanaged link with lumped amplification and
an amplifier spacing of 60 km, the SE after 80 spans can be be increased from
4.5 to 4.8 bit/s/Hz/polarization, or the reach raised up to 100 spans (+25%)
for a fixed SE.Comment: Submitted to Journal of Lightwave Technolog
Development of a dc-ac power conditioner for wind generator by using neural network
This project present of development single phase DC-AC converter for wind
generator application. The mathematical model of the wind generator and Artificial
Neural Network control for DC-AC converter is derived. The controller is designed to
stabilize the output voltage of DC-AC converter. To verify the effectiveness of the
proposal controller, both simulation and experimental are developed. The simulation and
experimental result show that the amplitude of output voltage of the DC-AC converter
can be controlled
A fourth-order Runge-Kutta in the interaction picture method for coupled nonlinear Schrodinger equation
A fourth-order Runge-Kutta in the interaction picture (RK4IP) method is
presented for solving the coupled nonlinear Schrodinger equation (CNLSE) that
governs the light propagation in optical fibers with randomly varying
birefringence. The computational error of RK4IP is caused by the fourth-order
Runge-Kutta algorithm, better than the split-step approximation limited by the
step size. As a result, the step size of RK4IP can have the same order of
magnitude as the dispersion length and/or the nonlinear length of the fiber,
provided the birefringence effect is small. For communication fibers with
random birefringence, the step size of RK4IP can be orders of magnitude larger
than the correlation length and the beating length of the fibers, depending on
the interaction between linear and nonlinear effects. Our approach can be
applied to the fibers having the general form of local birefringence and treat
the Kerr nonlinearity without approximation. For the systems with realistic
parameters, the RK4IP results are consistent with those using Manakov-PMD
approximation. However, increased interaction between the linear and nonlinear
terms in CNLSE leads to increased discrepancy between RK4IP and Manakov-PMD
approximation.Comment: 12 pages, 4 figures, 1 Table, submitted to Optics Express
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