Diffusion LMS networks in the presence of noisy nodes: A convergence rate and MSD analysis

Author

de Paula, Amanda ; Panazio, Cristiano

Author_Institution

Dept. de Eng. de Telecomun. e Controle (PTC), Univ. of Sao Paulo SP, Sao Paulo, Brazil

fYear

2013

fDate

22-25 Sept. 2013

Firstpage

1

Lastpage

6

Abstract

In this article, we provide a detailed analysis of the diffusion least mean square algorithm in the specific context where each node in the network presents different SNR values. We show, through an eigenvalue analysis, the condition that the algorithm step-size values should obey in order to provide a given convergence rate. Under this condition, it is shown how to set the algorithm step-size in each node that lead to the minimum mean square deviation. We also provide simulation results that corroborate our theoretical analysis.

Keywords

eigenvalues and eigenfunctions; least mean squares methods; wireless sensor networks; MSD analysis; convergence rate; diffusion LMS networks; diffusion least mean square algorithm; eigenvalue analysis; minimum mean square deviation; noisy nodes; Convergence; Eigenvalues and eigenfunctions; Least squares approximations; Mesh networks; Noise; Noise measurement; Vectors; adaptive algorithm; diffusion LMS; eigenvalue analysis; wireless sensor network;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on

Conference_Location

Southampton

ISSN

1551-2541

Type

conf

DOI

10.1109/MLSP.2013.6661918

Filename

6661918