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arXiv · 2404.04558

EVT-enriched Radio Maps for URLLC

Dian Echevarría Pérez·Onel L. Alcaraz López·Hirley Alves
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Abstract

This paper introduces a sophisticated and adaptable framework combining extreme value theory with radio maps to spatially model extreme channel conditions accurately. Utilising existing signal-to-noise ratio (SNR) measurements and leveraging Gaussian processes, our approach predicts the tail of the SNR distribution, which entails estimating the parameters of a generalised Pareto distribution, at unobserved locations. This innovative method offers a versatile solution adaptable to various resource allocation challenges in ultra-reliable low-latency communications. We evaluate the performance of this method in a rate maximisation problem with defined outage constraints and compare it with a benchmark in the literature. Notably, the proposed approach meets the outage demands in a larger percentage of the coverage area and reaches higher transmission rates.

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Dian Echevarría Pérez, Onel L. Alcaraz López, Hirley Alves. 2024-04-06. EVT-enriched Radio Maps for URLLC. https://arxiv.org/abs/2404.04558

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