Separation Theorems And Partial Orderings For Sensor Network Problems
 Michael C. Gastpar
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In this chapter, we discuss informationtheoretic techniques to understand sensor network performance. From an informationtheoretic perspective, sensor network problems are typically joint sourcechannel coding problems: The goal is to recover an approximate version of the underlying source information (by contrast to, for example, the standard channel coding problems where the goal is to communicate bits at the smallest possible error probability). Hence, the overall encoding process maps a sequence of source observations into a suitable sequence of channel inputs in such a way that the decoder, upon observing a noisy version of that sequence, can get an estimate of the source observations at the highest possible fidelity. Successful code constructions must exploit the structure of the underlying source (and the mechanism by which the source is observed) and the communication channel. Designing codes that simultaneously achieve both should be expected to be a rather difficult task, and it is therefore somewhat surprising that Shannon [27] found a very elegant solution for the case of pointtopoint communication (as long as both the source and the channel are stationary and ergodic, and cost and fidelity are assessed by perletter criteria). The solution consists in a separation of the overall task into two separate tasks. Specifically, an optimal communication strategy can be designed in two parts, a source code, exploiting the structure of the source and the observation process, followed by a channel code, exploiting the structure of the communication channel. The two stages are connected by a universal interface  bits that does not depend on the precise structure. For the purpose of this chapter, we will refer to such an architecture as separationbased.
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 Title
 Separation Theorems And Partial Orderings For Sensor Network Problems
 Book Title
 Networked Sensing Information and Control
 Book Part
 3
 Pages
 pp 197219
 Copyright
 2008
 DOI
 10.1007/9780387688459_8
 Print ISBN
 9780387688435
 Online ISBN
 9780387688459
 Publisher
 Springer US
 Copyright Holder
 SpringerVerlag US
 Additional Links
 Topics
 Industry Sectors
 eBook Packages
 Editors

 Venkatesh Saligrama ^{(1)}
 Editor Affiliations

 1. Boston University
 Authors

 Michael C. Gastpar ^{(2)}
 Author Affiliations

 2. University of California, 94704, Berkeley, CA, USA
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