Computer Science – Information Theory
Scientific paper
2009-11-12
Computer Science
Information Theory
42 pages, 9 figures, submitted to IEEE transactions on Information Theory
Scientific paper
We consider the asymmetric multilevel diversity (A-MLD) coding problem, where a set of $2^K-1$ information sources, ordered in a decreasing level of importance, is encoded into $K$ messages (or descriptions). There are $2^K-1$ decoders, each of which has access to a non-empty subset of the encoded messages. Each decoder is required to reproduce the information sources up to a certain importance level depending on the combination of descriptions available to it. We obtain a single letter characterization of the achievable rate region for the 3-description problem. In contrast to symmetric multilevel diversity coding, source-separation coding is not sufficient in the asymmetric case, and ideas akin to network coding need to be used strategically. Based on the intuitions gained in treating the A-MLD problem, we derive inner and outer bounds for the rate region of the asymmetric Gaussian multiple description (MD) problem with three descriptions. Both the inner and outer bounds have a similar geometric structure to the rate region template of the A-MLD coding problem, and moreover, we show that the gap between them is small, which results in an approximate characterization of the asymmetric Gaussian three description rate region.
Diggavi Suhas N.
Mohajer Soheil
Tian Chao
No associations
LandOfFree
Asymmetric Multilevel Diversity Coding and Asymmetric Gaussian Multiple Descriptions does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Asymmetric Multilevel Diversity Coding and Asymmetric Gaussian Multiple Descriptions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Asymmetric Multilevel Diversity Coding and Asymmetric Gaussian Multiple Descriptions will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-150373