Proper determination of the transmission rate in ultra-reliable low latency communication (URLLC) needs to incorporate a confidence interval (CI) for the estimated parameters due to the large amount of data required for their accurate estimation. In this paper, we propose a framework based on the extreme value theory (EVT) for determining the transmission rate along with its corresponding CI for an ultra-reliable communication system. This framework consists of characterizing the statistics of extreme events by fitting the generalized Pareto distribution (GPD) to the channel tail, deriving the GPD parameters and their associated CIs, and obtaining the transmission rate within a confidence interval. Based on the data collected within the engine compartment of Fiat Linea, we demonstrate the accuracy of the estimated rate obtained through the EVT-based framework considering the confidence interval for the GPD parameters. Additionally, we show that proper estimation of the transmission rate based on the proposed framework requires a lower number of samples compared to the traditional extrapolation-based approaches.

翻译：超可靠低时延通信（URLLC）中传输速率的准确确定需要为估计参数引入置信区间（CI），这是因为精确估计这些参数需要大量数据。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系统的传输速率及其对应的置信区间。该框架包含以下步骤：通过将广义帕累托分布（GPD）拟合至信道尾部来表征极端事件的统计特性，推导GPD参数及其相关置信区间，并在置信区间内获取传输速率。基于菲亚特Linea发动机舱内采集的数据，我们验证了在考虑GPD参数置信区间的情况下，基于EVT框架所估计速率的准确性。此外，研究表明，与传统外推方法相比，基于所提框架准确估计传输速率所需的样本数量更少。