1,006 research outputs found
Stochastic Digital Backpropagation with Residual Memory Compensation
Stochastic digital backpropagation (SDBP) is an extension of digital
backpropagation (DBP) and is based on the maximum a posteriori principle. SDBP
takes into account noise from the optical amplifiers in addition to handling
deterministic linear and nonlinear impairments. The decisions in SDBP are taken
on a symbol-by-symbol (SBS) basis, ignoring any residual memory, which may be
present due to non-optimal processing in SDBP. In this paper, we extend SDBP to
account for memory between symbols. In particular, two different methods are
proposed: a Viterbi algorithm (VA) and a decision directed approach. Symbol
error rate (SER) for memory-based SDBP is significantly lower than the
previously proposed SBS-SDBP. For inline dispersion-managed links, the VA-SDBP
has up to 10 and 14 times lower SER than DBP for QPSK and 16-QAM, respectively.Comment: 7 pages, accepted to publication in 'Journal of Lightwave Technology
(JLT)
Improved Lower Bounds on Mutual Information Accounting for Nonlinear Signal-Noise Interaction
In fiber-optic communications, evaluation of mutual information (MI) is still
an open issue due to the unavailability of an exact and mathematically
tractable channel model. Traditionally, lower bounds on MI are computed by
approximating the (original) channel with an auxiliary forward channel. In this
paper, lower bounds are computed using an auxiliary backward channel, which has
not been previously considered in the context of fiber-optic communications.
Distributions obtained through two variations of the stochastic digital
backpropagation (SDBP) algorithm are used as auxiliary backward channels and
these bounds are compared with bounds obtained through the conventional digital
backpropagation (DBP). Through simulations, higher information rates were
achieved with SDBP, {which can be explained by the ability of SDBP to account
for nonlinear signal--noise interactionsComment: 8 pages, 5 figures, accepted for publication in Journal of Lightwave
Technolog
Coherent 100G Nonlinear Compensation with Single-Step Digital Backpropagation
Enhanced-SSFM digital backpropagation (DBP) is experimentally demonstrated
and compared to conventional DBP. A 112 Gb/s PM-QPSK signal is transmitted over
a 3200 km dispersion-unmanaged link. The intradyne coherent receiver includes
single-step digital backpropagation based on the enhanced-SSFM algorithm. In
comparison, conventional DBP requires twenty steps to achieve the same
performance. An analysis of the computational complexity and structure of the
two algorithms reveals that the overall complexity and power consumption of DBP
are reduced by a factor of 16 with respect to a conventional implementation,
while the computation time is reduced by a factor of 20. As a result, the
proposed algorithm enables a practical and effective implementation of DBP in
real-time optical receivers, with only a moderate increase of the computational
complexity, power consumption, and latency with respect to a simple
feed-forward equalizer for dispersion compensation.Comment: This work has been presented at Optical Networks Design & Modeling
(ONDM) 2015, Pisa, Italy, May 11-14, 201
Information Transmission using the Nonlinear Fourier Transform, Part III: Spectrum Modulation
Motivated by the looming "capacity crunch" in fiber-optic networks,
information transmission over such systems is revisited. Among numerous
distortions, inter-channel interference in multiuser wavelength-division
multiplexing (WDM) is identified as the seemingly intractable factor limiting
the achievable rate at high launch power. However, this distortion and similar
ones arising from nonlinearity are primarily due to the use of methods suited
for linear systems, namely WDM and linear pulse-train transmission, for the
nonlinear optical channel. Exploiting the integrability of the nonlinear
Schr\"odinger (NLS) equation, a nonlinear frequency-division multiplexing
(NFDM) scheme is presented, which directly modulates non-interacting signal
degrees-of-freedom under NLS propagation. The main distinction between this and
previous methods is that NFDM is able to cope with the nonlinearity, and thus,
as the the signal power or transmission distance is increased, the new method
does not suffer from the deterministic cross-talk between signal components
which has degraded the performance of previous approaches. In this paper,
emphasis is placed on modulation of the discrete component of the nonlinear
Fourier transform of the signal and some simple examples of achievable spectral
efficiencies are provided.Comment: Updated version of IEEE Transactions on Information Theory, vol. 60,
no. 7, pp. 4346--4369, July, 201
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
Nonlinear digital compensation for spatial multiplexing systems
We review the latest advances on digital backward-propagation for the compensation of inter-channel nonlinear interference in spatial- and wavelength-multiplexed systems. Different solution methods of the multimode Schrödinger equation are compared for challenging linear mode coupling and differential mode delay conditions, highlighting the significant relaxation of the step size requirements provided by the separate-channels approach
Deep Neural Network Equalization for Optical Short Reach Communication
Nonlinear distortion has always been a challenge for optical communication due to the
nonlinear transfer characteristics of the ïŹber itself. The next frontier for optical communication is a
second type of nonlinearities, which results from optical and electrical components. They become the
dominant nonlinearity for shorter reaches. The highest data rates cannot be achieved without effective
compensation. A classical countermeasure is receiver-side equalization of nonlinear impairments
and memory effects using Volterra series. However, such Volterra equalizers are architecturally
complex and their parametrization can be numerical unstable. This contribution proposes an
alternative nonlinear equalizer architecture based on machine learning. Its performance is evaluated
experimentally on coherent 88 Gbaud dual polarization 16QAM 600 Gb/s back-to-back measurements.
The proposed equalizers outperform Volterra and memory polynomial Volterra equalizers up to 6th
orders at a target bit-error rate (BER) of 10
â2
by 0.5 dB and 0.8 dB in optical signal-to-noise ratio
(OSNR), respectively
On the Implementation Complexity of Digital Full-Duplex Self-Interference Cancellation
In-band full-duplex systems promise to further increase the throughput of
wireless systems, by simultaneously transmitting and receiving on the same
frequency band. However, concurrent transmission generates a strong
self-interference signal at the receiver, which requires the use of
cancellation techniques. A wide range of techniques for analog and digital
self-interference cancellation have already been presented in the literature.
However, their evaluation focuses on cases where the underlying physical
parameters of the full-duplex system do not vary significantly. In this paper,
we focus on adaptive digital cancellation, motivated by the fact that physical
systems change over time. We examine some of the different cancellation methods
in terms of their performance and implementation complexity, considering the
cost of both cancellation and training. We then present a comparative analysis
of all these methods to determine which perform better under different system
performance requirements. We demonstrate that with a neural network approach,
the reduction in arithmetic complexity for the same cancellation performance
relative to a state-of-the-art polynomial model is several orders of magnitude.Comment: Presented at the 2020 Asilomar Conference for Signals, Systems, and
Computer
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