Minimum energy decentralized estimation in sensor network with correlated sensor noise

Alexey Krasnopeev, Jin Jun Xiao, Zhi-Quan Luo

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

9 Scopus citations

Abstract

We consider the problem of a single parameter estimation by a sensor network with a fusion center (FC). Sensor observations are corrupted by additive noises which can have arbitrary spatial correlation. Due to a bandwidth constraint each sensor is only able to transmit a finite number of bits. The fusion center combines messages from the sensors to produce a parameter estimator, which is required to have Mean Square Error (MSE) within a constant factor of that of the Best Linear Unbiased Estimator (BLUE). We show that total sensor transmitted power can be minimized while meeting target MSE requirement if quantization levels are determined jointly by the fusion center using the knowledge of noise covariance matrix. By numerical examples we show that energy saving up to 70% can be achieved when compared to uniform quantization strategy when each sensor generates the same number of bits.

Original languageEnglish (US)
Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing,ICASSP '05 - Proceedings - Audio and ElectroacousticsSignal Processing for Communication
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)0780388747, 9780780388741
DOIs
StatePublished - Jan 1 2005
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: Mar 18 2005Mar 23 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeIII
ISSN (Print)1520-6149

Other

Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
CountryUnited States
CityPhiladelphia, PA
Period3/18/053/23/05

Fingerprint Dive into the research topics of 'Minimum energy decentralized estimation in sensor network with correlated sensor noise'. Together they form a unique fingerprint.

Cite this