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Channel aware adaptive quantization for target localization in wireless sensor networks

机译:用于无线传感器网络中目标定位的信道感知自适应量化

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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位的量化方案问题。首先,提出了一种用于目标位置估计的感知信道的自适应量化方案,本地传感器节点根据一种基于位置的信息序列动态调整其量化阈值。该方案合并了传感器和融合中心之间不完善的无线信道的统计信息。此外,得出适当的最大似然估计器(MLE)和性能指标Cramér-Rao下界(CRLB)。仿真结果表明,适当的CRLB小于固定量化通道感知的CRLB,并且当传感器数量足够大时,所提出的MLE将接近其CRLB。

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