27,193 research outputs found
Information Networks with in-Block Memory
A class of channels is introduced for which there is memory inside blocks of
a specified length and no memory across the blocks. The multi-user model is
called an information network with in-block memory (NiBM). It is shown that
block-fading channels, channels with state known causally at the encoder, and
relay networks with delays are NiBMs. A cut-set bound is developed for NiBMs
that unifies, strengthens, and generalizes existing cut bounds for discrete
memoryless networks. The bound gives new finite-letter capacity expressions for
several classes of networks including point-to-point channels, and certain
multiaccess, broadcast, and relay channels. Cardinality bounds on the random
coding alphabets are developed that improve on existing bounds for channels
with action-dependent state available causally at the encoder and for relays
without delay. Finally, quantize-forward network coding is shown to achieve
rates within an additive gap of the new cut-set bound for linear, additive,
Gaussian noise channels, symmetric power constraints, and a multicast session.Comment: Paper to appear in the IEEE Transactions on Information Theor
High-Cardinality Geometrical Constellation Shaping for the Nonlinear Fibre Channel
This paper presents design methods for highly efficient optimisation of
geometrically shaped constellations to maximise data throughput in optical
communications. It describes methods to analytically calculate the
information-theoretical loss and the gradient of this loss as a function of the
input constellation shape. The gradients of the \ac{MI} and \ac{GMI} are
critical to the optimisation of geometrically-shaped constellations. It
presents the analytical derivative of the achievable information rate metrics
with respect to the input constellation. The proposed method allows for
improved design of higher cardinality and higher-dimensional constellations for
optimising both linear and nonlinear fibre transmission throughput.
Near-capacity achieving constellations with up to 8192 points for both 2 and 4
dimensions, with generalised mutual information (GMI) within 0.06 bit/2Dsymbol
of additive white Gaussian noise channel (AWGN) capacity, are presented.
Additionally, a design algorithm reducing the design computation time from days
to minutes is introduced, allowing the presentation of optimised constellations
for both linear AWGN and nonlinear fibre channels for a wide range of
signal-to-noise ratios
Distributed Structure: Joint Expurgation for the Multiple-Access Channel
In this work we show how an improved lower bound to the error exponent of the
memoryless multiple-access (MAC) channel is attained via the use of linear
codes, thus demonstrating that structure can be beneficial even in cases where
there is no capacity gain. We show that if the MAC channel is modulo-additive,
then any error probability, and hence any error exponent, achievable by a
linear code for the corresponding single-user channel, is also achievable for
the MAC channel. Specifically, for an alphabet of prime cardinality, where
linear codes achieve the best known exponents in the single-user setting and
the optimal exponent above the critical rate, this performance carries over to
the MAC setting. At least at low rates, where expurgation is needed, our
approach strictly improves performance over previous results, where expurgation
was used at most for one of the users. Even when the MAC channel is not
additive, it may be transformed into such a channel. While the transformation
is lossy, we show that the distributed structure gain in some "nearly additive"
cases outweighs the loss, and thus the error exponent can improve upon the best
known error exponent for these cases as well. Finally we apply a similar
approach to the Gaussian MAC channel. We obtain an improvement over the best
known achievable exponent, given by Gallager, for certain rate pairs, using
lattice codes which satisfy a nesting condition.Comment: Submitted to the IEEE Trans. Info. Theor
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