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The critical speeds and radii for converage in sensor networks

注意:本论文已在《the 2007 International Conference on Intelligent Computing (ICIC 2007)》发表
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ZANG Chuan-zhi1,2  LIANG Wei1  YU Hai-bin1
(1.Shenyang Institute Automation,Chinese Academy of Sciences,Shenyang 110016;
2.Graduate School of the Chinese Academy of Sciences,Beijing 100049,China) 

Abstract: It is well known that localization plays an important role in wireless sensor network applications. There are two categories of localization approaches, such as range-based and range-free. RSSI(Received Signal Strength Indicator)-based method is in the first category. Three RSSI-based distance estimators, Biased Estimator (BE), Unbiased Estimator (UE) and Maximal Likelihood Estimator (MLE), are presented to calculate the distance. The biased estimator is the existing method which is used extensively in the literatures, while the unbiased estimator and maximal likelihood estimator are two new estimators developed in this paper. The probabilistic analysis of those estimators is done to compare the performance among them. The probabilistic analysis and simulations show that under some condition we should choose unbiased estimator and under some other condition we should choose MLE.

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本站收录的本文作者的其他论文:

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4、Target Tracking based on the Dynamic Cluster Method in the Acoustic Sensor Network

5、无线传感器网络动态协同任务分配机制

6、The Probabilistic Analysis of Distance Estimators in Wireless Sensor Network

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