DocumentCode :
2170774
Title :
Reduced-complexity bandwidth-constrained distributed estimation for wireless sensor networks
Author :
Jacobs, Trent ; Minn, Hlaing ; Al-Dhahir, Naofal
Author_Institution :
Univ. of Texas at Dallas, Dallas, TX
fYear :
2007
fDate :
April 30 2007-May 2 2007
Firstpage :
1
Lastpage :
5
Abstract :
While elegant in form, the maximum likelihood estimator (MLE) for heavily bandwidth-constrained distributed estimation in Gaussian noise is computationally expensive to implement. We consider an alternative estimator for this case which requires far less computational complexity, yet performs close to the MLE under the same operating conditions.
Keywords :
Gaussian noise; bandwidth compression; maximum likelihood estimation; wireless sensor networks; Gaussian noise; maximum likelihood estimator; reduced-complexity bandwidth-constrained distributed estimation; wireless sensor networks; Bandwidth; Computational complexity; Computer networks; Distributed computing; Gaussian noise; Maximum likelihood estimation; Parameter estimation; Power transmission; Sensor fusion; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sarnoff Symposium, 2007 IEEE
Conference_Location :
Nassau Inn, Princeton, NJ
Print_ISBN :
978-1-4244-2483-2
Type :
conf
DOI :
10.1109/SARNOF.2007.4567319
Filename :
4567319
Link To Document :
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