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