DocumentCode
77551
Title
High SNR Linear Estimation of Vector Sources
Author
Behbahani, Alireza S. ; Eltawil, Ahmed M. ; Jafarkhani, Hamid
Author_Institution
Center for Pervasive Commun. & Comput., Univ. of California, Irvine, Irvine, CA, USA
Volume
3
Issue
6
fYear
2014
fDate
Dec. 2014
Firstpage
581
Lastpage
584
Abstract
In this letter, we extend our prior work and consider decentralized estimation of unknown random vectors under high observation signal-to-noise ratio (SNR). A linear model is considered for decentralized estimation of vector sources. Observation models and sensor operations are both linear. Furthermore, the channel between the wireless sensors and fusion center (FC) is a coherent multiple access channel (MAC). Each sensor observes a different vector source. Sensors are designed to minimize the total mean square error (MSE) at the FC subject to the individual transmit power constraints at the sensors. We first provide the solution for scalar sources under high observation SNR regime. Then, we use the provided solution for scalar sources and extend it to the case of vector sources.
Keywords
mean square error methods; sensor fusion; wireless channels; wireless sensor networks; FC; coherent MAC; coherent multiple access channel; fusion center; power transmission; scalar source; signal-to-noise ratio; total MSE minimization; total mean square error minimization; unknown random vector source decentralized estimation; vector source high SNR linear estimation; wireless sensor network; Algorithm design and analysis; Covariance matrices; Estimation; Noise measurement; Signal to noise ratio; Wireless sensor networks; Distributed estimation; multiple access channel; wireless sensor networks;
fLanguage
English
Journal_Title
Wireless Communications Letters, IEEE
Publisher
ieee
ISSN
2162-2337
Type
jour
DOI
10.1109/LWC.2014.2359210
Filename
6905740
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