50 research outputs found
Joint Wyner-Ziv/Dirty Paper coding by modulo-lattice modulation
The combination of source coding with decoder side-information (Wyner-Ziv
problem) and channel coding with encoder side-information (Gel'fand-Pinsker
problem) can be optimally solved using the separation principle. In this work
we show an alternative scheme for the quadratic-Gaussian case, which merges
source and channel coding. This scheme achieves the optimal performance by a
applying modulo-lattice modulation to the analog source. Thus it saves the
complexity of quantization and channel decoding, and remains with the task of
"shaping" only. Furthermore, for high signal-to-noise ratio (SNR), the scheme
approaches the optimal performance using an SNR-independent encoder, thus it is
robust to unknown SNR at the encoder.Comment: Submitted to IEEE Transactions on Information Theory. Presented in
part in ISIT-2006, Seattle. New version after revie
On the Reliability Function of Distributed Hypothesis Testing Under Optimal Detection
The distributed hypothesis testing problem with full side-information is
studied. The trade-off (reliability function) between the two types of error
exponents under limited rate is studied in the following way. First, the
problem is reduced to the problem of determining the reliability function of
channel codes designed for detection (in analogy to a similar result which
connects the reliability function of distributed lossless compression and
ordinary channel codes). Second, a single-letter random-coding bound based on a
hierarchical ensemble, as well as a single-letter expurgated bound, are derived
for the reliability of channel-detection codes. Both bounds are derived for a
system which employs the optimal detection rule. We conjecture that the
resulting random-coding bound is ensemble-tight, and consequently optimal
within the class of quantization-and-binning schemes
Colored-Gaussian Multiple Descriptions: Spectral and Time-Domain Forms
It is well known that Shannon's rate-distortion function (RDF) in the colored
quadratic Gaussian (QG) case can be parametrized via a single Lagrangian
variable (the "water level" in the reverse water filling solution). In this
work, we show that the symmetric colored QG multiple-description (MD) RDF in
the case of two descriptions can be parametrized in the spectral domain via two
Lagrangian variables, which control the trade-off between the side distortion,
the central distortion, and the coding rate. This spectral-domain analysis is
complemented by a time-domain scheme-design approach: we show that the
symmetric colored QG MD RDF can be achieved by combining ideas of delta-sigma
modulation and differential pulse-code modulation. Specifically, two source
prediction loops, one for each description, are embedded within a common noise
shaping loop, whose parameters are explicitly found from the spectral-domain
characterization.Comment: Accepted for publications in the IEEE Transactions on Information
Theory. Title have been shortened, abstract clarified, and paper
significantly restructure
Joint Unitary Triangularization for MIMO Networks
This work considers communication networks where individual links can be
described as MIMO channels. Unlike orthogonal modulation methods (such as the
singular-value decomposition), we allow interference between sub-channels,
which can be removed by the receivers via successive cancellation. The degrees
of freedom earned by this relaxation are used for obtaining a basis which is
simultaneously good for more than one link. Specifically, we derive necessary
and sufficient conditions for shaping the ratio vector of sub-channel gains of
two broadcast-channel receivers. We then apply this to two scenarios: First, in
digital multicasting we present a practical capacity-achieving scheme which
only uses scalar codes and linear processing. Then, we consider the joint
source-channel problem of transmitting a Gaussian source over a two-user MIMO
channel, where we show the existence of non-trivial cases, where the optimal
distortion pair (which for high signal-to-noise ratios equals the optimal
point-to-point distortions of the individual users) may be achieved by
employing a hybrid digital-analog scheme over the induced equivalent channel.
These scenarios demonstrate the advantage of choosing a modulation basis based
upon multiple links in the network, thus we coin the approach "network
modulation".Comment: Submitted to IEEE Tran. Signal Processing. Revised versio
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