Linear precoding for distributed estimation of correlated sources in WSN MIMO system

Ajib Setyo Arifin, Tomoaki Ohtsuki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

We consider distributed estimation of a random vector signal in a power constraint wireless sensor network (WSN) that follows multiple-input and multiple-output (MIMO) coherent multiple access channel model. We design linear coding matrices based on linear minimum mean squared error (LMMSE) fusion rule that accommodates correlated sources. We obtain a closed-form solution that follows water-filling strategy. We also derive a lower bound distortion to this model. Simulation results show that when the sources are more correlated, the distortion in terms of mean squared error (MSE) degrades. By taking into account the effects of correlation, observation, and channel matrices, the proposed method performs better than equal power method.

Original languageEnglish
Title of host publication2013 IEEE 77th Vehicular Technology Conference, VTC Spring 2013 - Proceedings
DOIs
Publication statusPublished - 1 Dec 2013
Event2013 IEEE 77th Vehicular Technology Conference, VTC Spring 2013 - Dresden, Germany
Duration: 2 Jun 20135 Jun 2013

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Conference

Conference2013 IEEE 77th Vehicular Technology Conference, VTC Spring 2013
CountryGermany
CityDresden
Period2/06/135/06/13

Keywords

  • Distributed estimation
  • MIMO
  • Power constraint
  • Spatial correlated data
  • Water-filling
  • Wireless sensor network

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