稀疏树环境下无线传感器网络部署的路径损耗结果

Abdulaziz S. Alsayyari, Abdallah Aldosary
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引用次数: 7

摘要

本文提出了一个用于稀疏树环境下无线传感器网络(WSN)部署的大型射频测量数据集。这种测量通常是为了更好地评估和理解不同传播环境中的信号衰减。考虑到这种随机环境的理论路径损耗(PL)模型推导的复杂性,经验的PL模型是从特定场的现场测量中推导出来的。在本文中,经验PL模型已经在以前的工作中提出。然而,提供了更多关于模型推导的细节以及八个不同距离的接收信号强度(RSS)的变化。此外,将研究环境的经验PL模型与沙地地形、混凝土表面、稀疏树、茂密树和人造草坪5种WSN经验模型进行了比较。结果表明,不同环境在预测、指数和变异要素上存在显著差异。此外,将经验模型与流行的理论模型(即自由空间PL和双射线模型)进行了比较,结果表明这些理论模型在预测稀疏树环境下WSN部署的RSS时存在不准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path Loss Results for Wireless Sensor Network Deployment in a Sparse Tree Environment
This paper presents a large dataset of radio frequency (RF) measurements for wireless sensor network (WSN) deployment in a sparse tree environment. Such measurements are typically made for a better evaluation and understanding of signal attenuation in different propagation environments. Given the sophistication of theoretical path loss (PL) model derivation for such random environments, an empirical PL model is rather derived from in-field measurements for the specific field. In this paper, the empirical PL model has already been presented in a previous work. However, more details on model derivation as well as the variations of received signal strength (RSS) for eight different distances are provided. In addition, the empirical PL model of the investigated environment is compared with five empirical models of WSN, which are sand terrain, concrete surface, sparse tree, dense tree, and artificial turf. The results from the comparison of these different environments show significant differences in PL prediction, PL exponents, and variation elements. Furthermore, the empirical model is compared with popular theoretical models (i.e., free space PL and two-ray models), where the comparison shows an inaccuracy of these theoretical models in predicting RSS in WSN deployment in sparse tree environments.
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