Table of Contents
ISRN Sensor Networks
Volume 2013, Article ID 345457, 7 pages
Research Article

Water-Filling Solution for Distributed Estimation of Correlated Data in WSN MIMO System

Graduate School of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan

Received 3 June 2013; Accepted 12 August 2013

Academic Editors: A. Olteanu, A. Song, B. Tavli, and Y.-C. Wang

Copyright © 2013 Ajib Setyo Arifin and Tomoaki Ohtsuki. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We consider the distributed estimation of a random vector signal in a power constraint wireless sensor network (WSN) that follows a multiple-input and multiple-output (MIMO) coherent multiple access channel model. We design linear coding matrices based on linear minimum mean-square error (LMMSE) fusion rule that accommodates spatial correlated data. We obtain a closed-form solution that follows a water-filling strategy. We also derive a lower bound to this model. Simulation results show that when the data is more correlated, the distortion in terms of mean-square error (MSE) degrades. By taking into account the effects of correlation, observation, and channel matrices, the proposed method performs better than equal power method.