  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.
