分布式传感器网络中的Chernoff信息方位谱

Yifan Chen
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引用次数: 1

摘要

考虑一个分布式传感器网络(DSN),其中随机部署的传感器用于感兴趣现象(PoI)的二进制检测。数据融合中心(可能是传感器本身)使用直接获取的PoI数据和传输来自其他分布式传感器的关于PoI的二进制决策的无线通信信号来监视PoI。为了解决这个问题,我们研究了具有特定统计量的PoI,并提出了Chernoff信息方位角谱(CIAS)的建模范式,以提供dsn中渐近误差指数的紧凑的空间域表示。这种思想流派对定向多径信道的描述方法采用了类似的方法。然后根据传感器放置的几何建模详细阐述了上述理论框架。最后,我们简要解释了该方法在深空网络性能评估、仿真和信道测量方面的潜在应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chernoff information azimuth spectrum in distributed sensor networks
Consider a distributed sensor network (DSN) with randomly deployed sensors for binary detection of a phenomenon of interest (PoI). A data fusion center (which may be a sensor itself) monitors the PoI using both the directly acquired PoI data and the wireless communication signals conveying binary decisions about the PoI from other distributed sensors. To address this problem, we look into a PoI with specified statistics and present the modeling paradigm of Chernoff information azimuth spectrum (CIAS) to provide a compact, space-domain representation of asymptotic error exponents in DSNs. This school of thought applies an analogous approach to the description method of directional multipath channels. The above theoretical framework is then elaborated in light of geometrically-based modeling of sensor placement. Finally, we briefly explain the potential applications of the proposed methodology in terms of DSN performance evaluation, simulation and channel measurement.
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