Separation of Source-Network Coding and Channel Coding in Wireline Networks

Jalali, Shirin; Effros, Michelle

doi:10.1109/tit.2015.2397932

Cited by 2 publications

(2 citation statements)

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“…Proof: Gu [8], and Jalali and Effros [9] showed that in any network with any set of bounded distortion metrics, a rate is achievable for zero distortion between two of the variables, iff it is achievable with zero probability of error among the same variables. In other words, lossless reconstruction is achievable if and only if zero-distortion reconstruction is achievable.…”

Section: Resultsmentioning

confidence: 99%

Interactive function computation with reconstruction constraints

Rezagah

Erkip

2013

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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This paper investigates two-terminal interactive function computation with reconstruction constraints. Each terminal wants to compute a (possibly different) function of two correlated sources, but can only access one of the sources directly. In addition to distortion constraints at the terminals, each terminal is required to estimate the computed function value at the other terminal in a lossy fashion, leading to the constrained reconstruction constraint. A special case of constrained reconstruction is the common reconstruction constraint, in which both terminals agree on the functions computed with probability one. The terminals exchange information in multiple rate constrained communication rounds. A characterization of the multi-round rate-distortion region for the above problem with constrained reconstruction constraints is provided. To gain more insights and to highlight the value of interaction and order of communication, the rate-distortion region for computing various functions of jointly Gaussian sources according to common reconstruction constraints is studied. 896 978-1-4799-3410-2

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Section: Resultsmentioning

confidence: 99%

Interactive function computation with reconstruction constraints

Rezagah

Erkip

2013

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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“…Networks composed of more complicated components such as broadcast channels or multiple access channels are studied in [24], where network coding instances are shown to serve as upper and lower bounding models; under these results, the capacity of two distinct network coding networks bound, from above and below, respectively, the capacity of the original network. Further work in this line of study includes [25], which addresses memoryless networks that take as input dependent sources, and [26], which addresses the systematic design of upper and lower bounding models based on certain cut set bounds of the original components. The design of tight upper and lower bounding models for complex network components remains an open problem.…”

Section: B Information Theorymentioning

confidence: 99%

Is there a canonical network for network information theory?

Effros

Langberg

2014

2014 IEEE Information Theory Workshop (ITW 2014)

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In recent years, work has begun to emerge demonstrating intriguing relationships between seemingly disparate information theoretic problems. For example, recent results establish powerful ties between solutions for networks of memoryless channels and networks of noiseless links (network coding networks), between network coding networks in which every internal node can code and a particular subset of network coding networks in which only a single internal node can code (index coding networks), and between multiple multicast demands on memoryless networks and multiple unicast demands on memoryless networks. While the results vary widely, together, they hint at the potential for a unifying theory. In this work, we consider one possible framework for such a theory. Inspired by ideas from the field of computational complexity theory, the proposed framework generalizes definitions and techniques for reduction, completeness, and approximation to the information theoretic domain. One possible outcome from such a theory is a taxonomy of information theoretic problems where problems in the same taxonomic class share similar properties in terms of their code designs, capacities, or other forms of solution. Another potential outcome is the identification of small classes of network information theoretic problems whose solutions, were they available, would solve all information theoretic problems in a much larger class. A third potential outcome is the development of techniques by which approximate solution for one family of network information theoretic problems can be obtained from precise or approximate solution of another family of networks.

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Separation of Source-Network Coding and Channel Coding in Wireline Networks

Cited by 2 publications

References 20 publications

Interactive function computation with reconstruction constraints

Interactive function computation with reconstruction constraints

Is there a canonical network for network information theory?

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