The Gaussian Many-Help-One Distributed Source Coding Problem
| dc.creator | Tavildar, Saurabha | |
| dc.creator | Viswanath, Pramod | |
| dc.creator | Wagner, Aaron B. | |
| dc.date | 2008-05-13 | |
| dc.date.accessioned | 2026-07-07T09:38:36Z | |
| dc.date.available | 2026-07-07T09:38:36Z | |
| dc.description | Jointly Gaussian memoryless sources are observed at N distinct terminals. The goal is to efficiently encode the observations in a distributed fashion so as to enable reconstruction of any one of the observations, say the first one, at the decoder subject to a quadratic fidelity criterion. Our main result is a precise characterization of the rate-distortion region when the covariance matrix of the sources satisfies a "tree-structure" condition. In this situation, a natural analog-digital separation scheme optimally trades off the distributed quantization rate tuples and the distortion in the reconstruction: each encoder consists of a point-to-point Gaussian vector quantizer followed by a Slepian-Wolf binning encoder. We also provide a partial converse that suggests that the tree structure condition is fundamental. | |
| dc.identifier | https://arxiv.org/abs/0805.1857 | |
| dc.identifier | http://arxiv.org/abs/0805.1857 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/160868 | |
| dc.subject | Information Theory | |
| dc.title | The Gaussian Many-Help-One Distributed Source Coding Problem | |
| dc.type | text |