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Lossy source coding for a cascade communication system with side-informations

TLDR
Inner and outer bounds for the rate distortion region are provided in this work for general discrete memoryless sources and the same equivalence can be established between the well-known successive refinement problem and Yamamoto's cascade communication system, without relying on their rate-distortion characterization.
Abstract
We investigate source coding in a cascade communication system consisting of an encoder, a relay and an end terminal, where both the relay and the end terminal wish to reconstruct source $X$ with certain fidelities. Additionally, side-informations $Z$ and $Y$ are available at the relay and the end terminal, respectively. The side-information $Z$ at the relay is a physically degraded version of side-information $Y$ at the end terminal. Inner and outer bounds for the rate distortion region are provided in this work for general discrete memoryless sources. The rate distortion region is characterized when the source and side-informations are jointly Gaussian and physically degraded. The doubly symmetric binary source is also investigated and the inner and outer bounds are shown to coincide in certain distortion regimes. A complete equivalence of the rate-distortion region is established between the problem being considered and the side-information scalable source coding problem, when there is no side-information at the relay. As a byproduct, the same equivalence can be established between the well-known successive refinement problem and Yamamoto's cascade communication system, without relying on their rate-distortion characterization.

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References
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Journal ArticleDOI

The rate-distortion function for source coding with side information at the decoder

TL;DR: The quantity R \ast (d) is determined, defined as the infimum ofrates R such that communication is possible in the above setting at an average distortion level not exceeding d + \varepsilon .
Journal ArticleDOI

Successive refinement of information

TL;DR: It is shown that in order to achieve optimal successive refinement the necessary and sufficient conditions are that the solutions of the rate distortion problem can be written as a Markov chain and all finite alphabet signals with Hamming distortion satisfy these requirements.
Journal ArticleDOI

Successive refinement of information: characterization of the achievable rates

TL;DR: A model to describe a source with distortion no larger than /spl Delta//sub 1 and a more accurate description at distortion at R/sub 1.
Journal ArticleDOI

Rate distortion when side information may be absent

TL;DR: The problem is considered of encoding a discrete memoryless source when correlated side information may or may not be available to the decoder and an appropriately defined D -admissible rate is shown to equal R(D) when the side information sources satisfy a specified degradedness condition.
Journal ArticleDOI

Source coding theory for cascade and branching communication systems

TL;DR: The achievable rate region is established for the cascade systems and bounds are obtained for the branching systems and some examples are also included.
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