Decentralized estimation with correlated additive noise: Does dependency always imply redundancy?

Fangrong Peng, Biao Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This paper studies decentralized estimation with correlated observations. Focusing on the additive model with correlated Gaussian noises, we attempt to answer several distinct yet related questions in decentralized estimation: 1. When does correlation imply redundancy, i.e., incur performance degradation compared with that of independent observations; 2. What is the optimal quantizer structure that maximizes the Fisher information at the fusion center; 3. What is the preferred communication direction in a tandem fusion network involving correlated observations? It is shown that there exist different correlation regimes whose impacts on the estimation performance are in sharp contrast with each other. For the Gaussian model, it is established that quantizing the observation is optimal regardless of the correlation coefficients; this is true despite the fact that subsequent estimators may differ at the fusion center. Finally, it is always beneficial to have the better sensor (i.e., that has a higher SNR) to serve as a fusion center in a tandem fusion network for all correlation regimes.

Original languageEnglish (US)
Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages677-681
Number of pages5
ISBN (Print)9781479923908
DOIs
StatePublished - Jan 1 2013
Event2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 3 2013Nov 6 2013

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other2013 47th Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period11/3/1311/6/13

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Peng, F., & Chen, B. (2013). Decentralized estimation with correlated additive noise: Does dependency always imply redundancy? In Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers (pp. 677-681). [6810368] (Conference Record - Asilomar Conference on Signals, Systems and Computers). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2013.6810368