Journal article · Ahead of Print article
Understanding sub-GHz Signal Behaviour in Deep-Indoor Scenarios
Critical Internet of Things (IoT) services require seamless connectivity, which is not always simple to provide and particularly in deep-indoor scenarios, it can be even impossible in some cases. The existing outdoor-to-indoor path loss models lack the accuracy in the underground situations, thus IoT coverage planning in such areas cannot rely on robust tools and becomes a process of trial and error.
In this work, we derive and analyse various environmental features that can be useful in understanding sub-GHz deep-indoor signal propagation. Based on a large-scale field trial in an underground tunnel system, we formulate several parameters related to TX-RX distance and tunnel geometry. Through feature relevance studies in linear (Ordinary Least Squares (OLS) regression) and non-linear (Gaussian Process Regression) realms we show that 2D indoor distance and the distances to the tunnel walls may be useful in sub-GHz signal strength prediction in deep-indoor situations.
We construct a linear and a Gaussian Process model for indoor path-loss prediction that outperform the 3rd Generation Partnership Project (3GPP) model by 1.8 dB and 4.1 dB, respectively.
Language: | English |
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Publisher: | IEEE |
Year: | 2021 |
Pages: | 6746-6756 |
ISSN: | 23722541 and 23274662 |
Types: | Journal article and Ahead of Print article |
DOI: | 10.1109/JIOT.2020.3027829 |
ORCIDs: | Malarski, Krzysztof Mateusz , Christiansen, Henrik Lehrmann , Ruepp, Sarah Renée and 0000-0003-0056-4503 |