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Path-loss modelling in deep-indoor scenarios is a difficult task. On onehand, the theoretical formulae solely dependent on transmitter-receiverdistance are too simple; on the other hand, discovering all significant factorsaffecting the loss of signal power in a given situation may often beinfeasible. In this paper, we experimentally investigate the influence ofdeep-indoor features such as indoor depth, indoor distance and distance to theclosest tunnel corridor and the effect on received power using NB-IoT. Wedescribe a measurement campaign performed in a system of long undergroundtunnels, and we analyse linear regression models involving the engineeredfeatures. We show that the current empirical models for NB-IoT signalattenuation are inaccurate in a deep-indoor scenario. We observe that 1) indoordistance and penetration depth do not explain the signal attenuation well andincrease the error of the prediction by 2-12 dB using existing models, and 2) apromising feature of average distance to the nearest corridor is identified.

Experimental Evaluation of Empirical NB-IoT Propagation Modelling in a Deep-Indoor Scenario