1,839 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
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