Consensus-based distributed estimation of random signals with wireless sensor networks

Ioannis D. Schizas, Georgios B. Giannakis

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

4 Scopus citations

Abstract

We deal with distributed linear minimum mean-square error (LMMSE) estimation of a random signal vector based on observations collected across a wireless sensor network (WSN). We cast this decentralized estimation problem as the solution of multiple constrained convex optimization subproblems. Using the method of multipliers in conjunction with a block coordinated descent approach we demonstrate how the resultant algorithm can be decomposed into a set of simpler tasks suitable for distributed implementation. Relative to existing alternatives, we establish that the novel decentralized algorithm guarantees convergence to the centralized LMMSE estimator for quite general (possibly nonlinear and/or non-Gaussian) data models. Through numerical experiments, we finally illustrate the convergence properties of the algorithm.

Original languageEnglish (US)
Title of host publicationConference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages530-534
Number of pages5
DOIs
StatePublished - Dec 1 2006
Event40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States
Duration: Oct 29 2006Nov 1 2006

Publication series

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

Other

Other40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
CountryUnited States
CityPacific Grove, CA
Period10/29/0611/1/06

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