"Quantization for Distributed Estimation in Large Scale Sensor Networks" P. Venkitasubramaniam, G. Mergen, L. Tong and A. Swami Third International Conference on Intelligent Sensing and Information Processing, Bangalore, India, Dec. 2005.
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 scorefunction 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.