Distributed MAP and LMMSE estimation of random signals using ad hoc wireless sensor networks with noisy links

Ioannis D. Schizas, Georgios B Giannakis, Alejandro Ribeiro

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

Abstract

Distributed estimation of random parameter vector is dealt with using ad hoc wireless sensor networks (WSNs). The decentralized estimation problem is cast as the solution of multiple convex optimization subproblems and the alternating direction method of multipliers is employed to derive algorithms which can be decomposed into a set of simpler tasks suitable for distributed implementation. Different from existing alternatives, the novel approach does not require knowing the desired estimator in closed-form as is generally the case with the maximum a posteriori estimator (MAP). In addition, a priori information is accounted for and sensor observations are allowed to be correlated. The resulting algorithms converge to the centralized estimators under ideal channel links, while they exhibit noise robustness provably established for the distributed linear minimum mean-square error estimator (LMMSE).

Original languageEnglish (US)
Title of host publicationSPAWC 2007 - 8th IEEE Workshop on Signal Advances in Wireless Communications
StatePublished - Dec 1 2007
Event8th IEEE Signal Processing Advances in Wireless Communications, SPAWC 2007 - Helsinki, Finland
Duration: Jun 17 2007Jun 20 2007

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

Other

Other8th IEEE Signal Processing Advances in Wireless Communications, SPAWC 2007
CountryFinland
CityHelsinki
Period6/17/076/20/07

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