DocumentCode :
2506597
Title :
Performance of statistical inference methods for the energy estimation of multiple sources
Author :
Couillet, Romain ; Guillaud, Maxime
Author_Institution :
Syst. Sci. & the Energy Challenge, Supelec, France
fYear :
2011
fDate :
28-30 June 2011
Firstpage :
673
Lastpage :
676
Abstract :
This article considers statistical inference of the transmit powers of multiple signal sources by a sensor network. Using random matrix methods, an exact expression of the posterior probability of the joint transmit powers is derived. This expression is used to implement the associated ML and MMSE detectors of the joint powers. These are compared for small system sizes against an asymptotically unbiased estimator obtained from large dimensional random matrix theory.
Keywords :
inference mechanisms; least mean squares methods; matrix algebra; maximum likelihood detection; probability; sensors; statistical analysis; ML detectors; MMSE detectors; asymptotic unbiased estimator; energy estimation; joint transmit powers; large dimensional random matrix theory; multiple signal sources; posterior probability; sensor network; statistical inference methods; Arrays; Eigenvalues and eigenfunctions; Joints; Maximum likelihood estimation; Mean square error methods; Tin;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing Workshop (SSP), 2011 IEEE
Conference_Location :
Nice
ISSN :
pending
Print_ISBN :
978-1-4577-0569-4
Type :
conf
DOI :
10.1109/SSP.2011.5967791
Filename :
5967791
Link To Document :
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