  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.
