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Quantization For Distributed Estimation in Large Scale Sensor Networks

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4 Author(s)
P. Venkitasubramaniam ; Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY ; G. Mergen ; Lang Tong ; A. Swami

We study the problem of quantization for distributed parameter estimation in large scale sensor networks. Assuming a maximum likelihood estimator at the fusion center, we show that the Fisher information is maximized by a score-function quantizer. This provides a tight bound on best possible MSE for any unbiased estimator. Furthermore, we show that for a general convex metric, the optimal quantizer belongs to the class of score function quantizers. We also discuss a few practical applications of our results in optimizing estimation performance in distributed and temporal estimation problems

Published in:

2005 3rd International Conference on Intelligent Sensing and Information Processing

Date of Conference:

14-17 Dec. 2005