arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2002.00565eess.SP
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面向超可靠通信的基于极值理论的无线信道建模

Wireless Channel Modeling Based on Extreme Value Theory for Ultra-Reliable Communications

Niloofar Mehrnia, Sinem Coleri

AI总结:

本文提出基于极值理论的无线信道建模方法,利用广义帕累托分布拟合接收功率下尾分布,在Fiat Linea发动机舱数据上显著优于传统外推方法,并将所需样本数减少约70万个。

摘要:

超可靠通信系统设计中的一个关键构建模块是能够捕捉由显著衰落引起的稀有事件统计特性的无线信道模型。本文提出了一种基于极值理论(EVT)的新方法,用于对超可靠通信中无线信道极端事件的行为进行统计建模。该方法包括以下技术:将接收功率的下尾分布拟合到广义帕累托分布(GPD),确定用于推导尾部统计量的最优阈值,确定利用GPD估计尾部统计量所需样本数的最优停止条件,以及最终评估所推导的帕累托模型的有效性。基于在Fiat Linea发动机舱内在各种发动机振动和驾驶场景下收集的数据,我们证明了所提出的方法对收集到的数据提供了最佳拟合,显著优于传统的基于外推的方法。此外,在所提出的方法中使用EVT将估计尾部统计量所需的样本数减少了约$7 \ imes 10^5$个。

英文摘要:

A key building block in the design of ultra-reliable communication systems is a wireless channel model that captures the statistics of rare events occurring due to significant fading. In this paper, we propose a novel methodology based on extreme value theory (EVT) to statistically model the behavior of extreme events in a wireless channel for ultra-reliable communication. This methodology includes techniques for fitting the lower tail distribution of the received power to the generalized Pareto distribution (GPD), determining the optimum threshold over which the tail statistics are derived, ascertaining the optimum stopping condition on the number of samples required to estimate the tail statistics by using GPD, and finally, assessing the validity of the derived Pareto model. Based on the data collected within the engine compartment of Fiat Linea under various engine vibrations and driving scenarios, we demonstrate that the proposed methodology provides the best fit to the collected data, significantly outperforming the conventional extrapolation-based methods. Moreover, the usage of the EVT in the proposed method decreases the required number of samples for estimating the tail statistics by about $7 \times 10^5$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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