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

被引：0
|
作者：
Weng, Yang [1 ]
机构：
[1] Sichuan Univ, Coll Math, Chengdu 610064, Sichuan, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2014年 / 2014卷
基金：
中国国家自然科学基金;
关键词：
DIMENSIONALITY REDUCTION; QUANTIZERS;
D O I：
10.1155/2014/932358
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
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页数：8
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