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Cram#x00E9;r-Rao lower bound for breakpoint distance estimation in a path-loss model

机译:Cramér-Rao在路径损耗模型中的断点距离估计下限

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摘要

This paper addresses the problem of determining the Cramér-Rao lower bound (CRLB) for the parameters and breakpoint distance in a Path-Loss Channel model for Received Signal Strength (RSS) measurements. The path loss model is usually assumed for corrupted RSS measurements due to the shadow fading channel feature. In this paper the two-slope path loss model is considered, in which RSS measurements are modeled differently for close and far distances. Closed-form expressions for the CRLB parameters are derived for unknown breakpoint distance. For unknown parameters and breakpoint distance value, a Bayesian estimation method is proposed. The CRLB is then compared with the performance of the herein proposed method. The comparison illustrates convergence and efficiency of the Bayesian estimator.
机译:本文解决了用于接收信号强度(RSS)测量的路径丢失信道模型中的参数和断点距离的Cramér-Rao下限(CRLB)的问题。由于阴影衰落信道特征,通常假设路径损耗模型通常用于损坏的RS测量。在本文中,考虑了双斜线损耗模型,其中RSS测量以不同的方式为近距离和远距离进行建模。用于CRLB参数的闭合表达式用于未知断点距离。对于未知的参数和断点距离值,提出了一种贝叶斯估计方法。然后将CRLB与本文提出的方法的性能进行比较。比较说明了贝叶斯估计器的收敛性和效率。

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