Extreme Value Theory Based Rate Selection for Ultra-Reliable Communications

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 ultrareliable 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.

Automated summary

This paper proposes a framework based on extreme value theory for determining the rate selection for ultra-reliable communications. By modeling the wireless channel and incorporating statistical data, the best fitting parameters for the tail distribution are estimated and integrated into the rate selection function. The selected rate is validated by computing the error probability.