Session 4A Senisor Networks
نویسنده
چکیده
oEE 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 scoreD 2 function quantizer. This provides a tight bound on best possible MSE for any unbiased estimator. Furthermore, we Y. 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 optif(Y, Y.) mizing estimation performance in distributed and temporal estimation problems. 0
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