Files in this item



application/pdf3243047.pdf (2MB)Restricted to U of Illinois
(no description provided)PDF


Title:Source and Channel Coding for Wireless Networks
Author(s):Tavildar, Saurabha R.
Doctoral Committee Chair(s):Viswanath, Pramod
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Engineering, Electronics and Electrical
Abstract:Then, motivated by applications in sensor networks, we study the problem of distributed source coding. Distributed source coding refers to the compression of correlated sources by encoders that are physically separated. The pioneering result of Slepian and Wolf states that the rate region for the lossless distributed source coding problem is as if the encoders were allowed to cooperate. We look at the natural generalization of this problem to sources with continuous alphabets. We model the sources as jointly Gaussian random variables and the distortion criterion as an average mean squared one. We are interested in obtaining the rate distortion region for this problem. We show that the natural strategy of point-to-point vector quantization followed by distributed compression by binning scheme of Slepian and Wolf is optimal in various instances of the problem. In particular, we focus on three instances of the problem. First, we characterize the rate distortion region for the two-terminal memoryless Gaussian source where the decoder is interested in two specific nonnegative linear combinations of a positively correlated vector Gaussian source. This includes the solution to the well-known separate distortion problem. Then, we model sources with memory as vector sources that are independent and identically distributed in time. We consider the vector Gaussian CEO problem where the vector observations are independent given an underlying vector random variable. We obtain an outer bound for the sum-rate of this problem that is tight for various instances of the problem including symmetric version. Finally, we characterize the rate region for an instance of the Gaussian many-help-one problem where there is an underlying Gaussian random variable that induces conditional independence between the observations.
Issue Date:2006
Description:91 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.
Other Identifier(s):(MiAaPQ)AAI3243047
Date Available in IDEALS:2015-09-25
Date Deposited:2006

This item appears in the following Collection(s)

Item Statistics