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Channel aware adaptive quantization for target localization in wireless sensor networks

机译:信道意识到无线传感器网络中目标定位的自适应量化

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This paper considers the problem of quantization schemes for source localization in wireless sensor networks. First, a channel-aware adaptive quantization scheme for target location estimation is proposed and local sensor nodes dynamically adjust their quantization thresholds according to a kind of position-based information sequences. The scheme incorporates the statistics of imperfect wireless channels between sensors and the fusion center. Furthermore, the appropriate maximum likelihood estimator (MLE) and the performance metric Cramér-Rao lower bound (CRLB) are derived. Simulation results are presented to show that the appropriated CRLB is less than the fixed-quantization channel-aware CRLB and the proposed MLE will approach its CRLB when the number of sensors is large enough.
机译:本文考虑了无线传感器网络中源定值的量化方案的问题。首先,提出了一种用于目标位置估计的频道感知自适应量化方案,并且本地传感器节点根据基于位置的信息序列的类型动态地调整它们的量化阈值。该方案包含传感器和融合中心之间的不完美无线信道的统计信息。此外,推导出适当的最大似然估计器(MLE)和性能度量CRAMÉR-RAO下限(CRLB)。提出了仿真结果表明,适当的CRLB小于固定量化信道感知CRLB,当传感器的数量足够大时,所提出的MLE将接近其CRLB。

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