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Towards a Characterization of Localization Performance in Networks with Random Geometries

机译:朝着随机几何形状的网络中的本地化性能的表征

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This paper introduces a paradigm shift in the way localization performance in wireless networks is analyzed. Currently, localization performance in networks is commonly benchmarked using the Cramér-Rao lower bound (CRLB), given a fixed geometry of anchor nodes and a target. By contrast, we consider networks with random geometries for which the CRLB itself becomes a random variable, and we seek a tractable expression for its distribution. The ultimate goal is to derive a complete statistical characterization of localization performance throughout an entire network via analysis, rather than resorting to simulation. This paper presents an initial step towards achieving this goal by using an approximation of the CRLB based on angles between anchor nodes. This facilitates the derivation of an accurate approximation of the distribution of the CRLB, conditioned on the number of hearable anchors.
机译:本文在分析了无线网络中的本地化性能方面介绍了范式转换。目前,在锚点节点和目标的固定几何形状,网络中的本地化性能通常使用Cramér-Rao下限(CRLB)进行基准测试。相比之下,我们考虑具有随机几何形状的网络,CRLB本身成为随机变量,我们为其分发寻求一个易诊表达。最终目标是通过分析来推导整个网络整个网络中的本地化性能的完整统计表征,而不是诉诸模拟。本文通过使用基于锚节点之间的角度来实现CRLB的近似来达到实现该目标的初始步骤。这有助于推导到CRLB的分布的准确近似,调节在可听见的锚点的数量上。

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