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

The unknown vector estimation problem with bandwidth constrained wireless sensor network is considered. In such networks, sensor nodesmake 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 nodemust 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. [ABSTRACT FROM AUTHOR]