Ultra-reliable low latency communication (URLLC) requires the packet error rate to be on the order of $10^{-9}$-$10^{-5}$. Determining the appropriate transmission rate to satisfy this ultra-reliability constraint requires deriving the statistics of the channel in the ultra-reliable region and then incorporating these statistics into the rate selection. In this paper, we propose a framework for determining the rate selection for ultra-reliable communications based on the extreme value theory (EVT). We first model the wireless channel at URLLC by estimating the parameters of the generalized Pareto distribution (GPD) best fitting to the tail distribution of the received powers, i.e., the power values below a certain threshold. Then, we determine the maximum transmission rate by incorporating the Pareto distribution into the rate selection function. Finally, we validate the selected rate by computing the resulting error probability. Based on the data collected within the engine compartment of Fiat Linea, we demonstrate the superior performance of the proposed methodology in determining the maximum transmission rate compared to the traditional extrapolation-based approaches.

翻译：超可靠低延迟通信（URLLC）要求误包率在$10^{-9}$-$10^{-5}$量级。为满足该超可靠约束确定合适的传输速率，需要推导超可靠区域内的信道统计特性，并将这些统计特性融入速率选择过程。本文提出一种基于极值理论（EVT）的框架，用于确定超可靠通信的速率选择方案。首先，通过估计广义帕累托分布（GPD）参数对URLLC无线信道进行建模，该分布最佳拟合接收功率的尾部分布（即低于特定阈值的功率值）。随后，将帕累托分布纳入速率选择函数以确定最大传输速率。最后，通过计算所得误码概率验证所选速率的有效性。基于菲亚特Linea发动机舱内采集的数据，我们证明所提方法在确定最大传输速率方面相比传统外推方法具有更优性能。