5,021 research outputs found
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
Capacity of a Nonlinear Optical Channel with Finite Memory
The channel capacity of a nonlinear, dispersive fiber-optic link is
revisited. To this end, the popular Gaussian noise (GN) model is extended with
a parameter to account for the finite memory of realistic fiber channels. This
finite-memory model is harder to analyze mathematically but, in contrast to
previous models, it is valid also for nonstationary or heavy-tailed input
signals. For uncoded transmission and standard modulation formats, the new
model gives the same results as the regular GN model when the memory of the
channel is about 10 symbols or more. These results confirm previous results
that the GN model is accurate for uncoded transmission. However, when coding is
considered, the results obtained using the finite-memory model are very
different from those obtained by previous models, even when the channel memory
is large. In particular, the peaky behavior of the channel capacity, which has
been reported for numerous nonlinear channel models, appears to be an artifact
of applying models derived for independent input in a coded (i.e., dependent)
scenario
Influence of Behavioral Models on Multiuser Channel Capacity
In order to characterize the channel capacity of a wavelength channel in a
wavelength-division multiplexed (WDM) system, statistical models are needed for
the transmitted signals on the other wavelengths. For example, one could assume
that the transmitters for all wavelengths are configured independently of each
other, that they use the same signal power, or that they use the same
modulation format. In this paper, it is shown that these so-called behavioral
models have a profound impact on the single-wavelength achievable information
rate. This is demonstrated by establishing, for the first time, upper and lower
bounds on the maximum achievable rate under various behavioral models, for a
rudimentary WDM channel model
Bounds on the Per-Sample Capacity of Zero-Dispersion Simplified Fiber-Optical Channel Models
A number of simplified models, based on perturbation theory, have been
proposed for the fiber-optical channel and have been extensively used in the
literature. Although these models are mainly developed for the low-power
regime, they are used at moderate or high powers as well. It remains unclear to
what extent the capacity of these models is affected by the simplifying
assumptions under which they are derived. In this paper, we consider single
channel data transmission based on three continuous-time optical models i) a
regular perturbative channel, ii) a logarithmic perturbative channel, and iii)
the stochastic nonlinear Schr\"odinger (NLS) channel. We apply two simplifying
assumptions on these channels to obtain analytically tractable discrete-time
models. Namely, we neglect the channel memory (fiber dispersion) and we use a
sampling receiver. These assumptions bring into question the physical relevance
of the models studied in the paper. Therefore, the results should be viewed as
a first step toward analyzing more realistic channels. We investigate the
per-sample capacity of the simplified discrete-time models. Specifically, i) we
establish tight bounds on the capacity of the regular perturbative channel; ii)
we obtain the capacity of the logarithmic perturbative channel; and iii) we
present a novel upper bound on the capacity of the zero-dispersion NLS channel.
Our results illustrate that the capacity of these models departs from each
other at high powers because these models yield different capacity pre-logs.
Since all three models are based on the same physical channel, our results
highlight that care must be exercised in using simplified channel models in the
high-power regime
Impact of 4D channel distribution on the achievable rates in coherent optical communication experiments
We experimentally investigate mutual information and generalized mutual
information for coherent optical transmission systems. The impact of the
assumed channel distribution on the achievable rate is investigated for
distributions in up to four dimensions. Single channel and wavelength division
multiplexing (WDM) transmission over transmission links with and without inline
dispersion compensation are studied. We show that for conventional WDM systems
without inline dispersion compensation, a circularly symmetric complex Gaussian
distribution is a good approximation of the channel. For other channels, such
as with inline dispersion compensation, this is no longer true and gains in the
achievable information rate are obtained by considering more sophisticated
four-dimensional (4D) distributions. We also show that for nonlinear channels,
gains in the achievable information rate can also be achieved by estimating the
mean values of the received constellation in four dimensions. The highest gain
for such channels is seen for a 4D correlated Gaussian distribution
Non-parametric Estimation of Mutual Information with Application to Nonlinear Optical Fibers
This paper compares and evaluates a set of non-parametric mutual information
estimators with the goal of providing a novel toolset to progress in the
analysis of the capacity of the nonlinear optical channel, which is currently
an open problem. In the first part of the paper, the methods of the study are
presented. The second part details their application to several
optically-related channels to highlight their features.Comment: This work has been submited to IEEE International Symposium on
Information Theor
On Achievable Rates for Long-Haul Fiber-Optic Communications
Lower bounds on mutual information (MI) of long-haul optical fiber systems
for hard-decision and soft-decision decoding are studied. Ready-to-use
expressions to calculate the MI are presented. Extensive numerical simulations
are used to quantify how changes in the optical transmitter, receiver, and
channel affect the achievable transmission rates of the system. Special
emphasis is put to the use of different quadrature amplitude modulation
formats, channel spacings, digital back-propagation schemes and probabilistic
shaping. The advantages of using MI over the prevailing -factor as a figure
of merit of coded optical systems are also highlighted.Comment: Hard decision mutual information analysis added, two typos correcte
Conditions for a Monotonic Channel Capacity
Motivated by results in optical communications, where the performance can
degrade dramatically if the transmit power is sufficiently increased, the
channel capacity is characterized for various kinds of memoryless vector
channels. It is proved that for all static point-to-point channels, the channel
capacity is a nondecreasing function of power. As a consequence, maximizing the
mutual information over all input distributions with a certain power is for
such channels equivalent to maximizing it over the larger set of input
distributions with upperbounded power. For interference channels such as
optical wavelength-division multiplexing systems, the primary channel capacity
is always nondecreasing with power if all interferers transmit with identical
distributions as the primary user. Also, if all input distributions in an
interference channel are optimized jointly, then the achievable sum-rate
capacity is again nondecreasing. The results generalizes to the channel
capacity as a function of a wide class of costs, not only power.Comment: This is an updated and expanded version of arXiv:1108.039
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