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Journal Articles IEEE Wireless Communications Year : 2023

Delivering Ultra-Reliable Low-Latency Communications via Statistical Radio Maps


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. 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. Lastly, several future directions and research challenges are also discussed.
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hal-04102867 , version 1 (06-12-2023)



Tobias Kallehauge, Anders Kalør, Pablo Ramírez-Espinosa, Maxime Guillaud, Petar Popovski. Delivering Ultra-Reliable Low-Latency Communications via Statistical Radio Maps. IEEE Wireless Communications, 2023, 30 (2), pp.14-20. ⟨10.1109/MWC.002.2200372⟩. ⟨hal-04102867⟩
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