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Mathematical Problems in Engineering
Volume 2014, Article ID 932358, 8 pages
Research Article

Data Reduction with Quantization Constraints for Decentralized Estimation in Wireless Sensor Networks

College of Mathematics, Sichuan University, Chengdu, Sichuan 610064, China

Received 22 August 2013; Revised 15 December 2013; Accepted 19 December 2013; Published 9 January 2014

Academic Editor: Shuli Sun

Copyright © 2014 Yang Weng. 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.


The unknown vector estimation problem with bandwidth constrained wireless sensor network is considered. In such networks, sensor nodes make distributed observations on the unknown vector and collaborate with a fusion center to generate a final estimate. Due to power and communication bandwidth limitations, each sensor node must compress its data and transmit to the fusion center. In this paper, both centralized and decentralized estimation frameworks are developed. The closed-form solution for the centralized estimation framework is proposed. The computational complexity of decentralized estimation problem is proven to be NP-hard and a Gauss-Seidel algorithm to search for an optimal solution is also proposed. Simulation results show the good performance of the proposed algorithms.