High reliability guarantees for Ultra-Reliable Low-Latency Communications (URLLC) require accurate knowledge of channel statistics, used as an input for rate selection. Exploiting the spatial consistency of channel statistics arises as a promising solution, allowing a base station to predict the propagation conditions and select the communication parameters for a new user from samples collected from previous users of the network. Based on this idea, this article provides a timely framework to exploit long-range channel spatial correlation through so-called statistical radio maps, enabling URLLC communications with given statistical guarantees. The framework is exemplified by predicting the channel capacity distribution both in a location-based radio map and in a latent space rendered by a channel chart, the latter being a localization-free approach based on channel state information (CSI). It is also shown how to use the maps to select the transmission rate in a new location that achieves a target level of reliability. Finally, several future directions and research challenges are also discussed.
@article{arxiv.2209.10927,
title = {Delivering Ultra-Reliable Low-Latency Communications via Statistical Radio Maps},
author = {Tobias Kallehauge and Anders E. Kalør and Pablo Ramírez-Espinosa and Maxime Guillaud and Petar Popovski},
journal= {arXiv preprint arXiv:2209.10927},
year = {2022}
}