DocumentCode :
1472216
Title :
Eigen-Inference for Energy Estimation of Multiple Sources
Author :
Couillet, Romain ; Silverstein, Jack W. ; Bai, Zhidong ; Debbah, Mérouane
Author_Institution :
Dept. of Syst. Sci., SUPELEC, Gif-sur-Yvette, France
Volume :
57
Issue :
4
fYear :
2011
fDate :
4/1/2011 12:00:00 AM
Firstpage :
2420
Lastpage :
2439
Abstract :
In this paper, a new method is introduced to blindly estimate the transmit power of multiple signal sources in multiantenna fading channels, when the number of sensing devices and the number of available samples are sufficiently large compared to the number of sources. Recent advances in the field of large dimensional random matrix theory are used that result in a simple and computationally efficient consistent estimator of the power of each source. A criterion to determine the minimum number of sensors and the minimum number of samples required to achieve source separation is then introduced. Simulations are performed that corroborate the theoretical claims and show that the proposed power estimator largely outperforms alternative power inference techniques.
Keywords :
antenna arrays; blind source separation; fading channels; matrix algebra; random processes; statistical analysis; alternative power inference techniques; blindly estimate; consistent estimator; eigen-inference; energy estimation; large dimensional random matrix theory; multiantenna fading channels; multiple signal sources; multiple sources; power estimator; sensing devices; source separation; transmit power; Covariance matrix; Eigenvalues and eigenfunctions; Estimation; Receiving antennas; Sensors; Transforms; Transmitting antennas; Cognitive radio; G-estimation; power estimation; random matrix theory; statistical inference;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2011.2109990
Filename :
5730563
Link To Document :
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