Path-loss modelling in deep-indoor scenarios is a difficult task. On one hand, the theoretical formulae solely dependent on transmitter-receiver distance are too simple; on the other hand, discovering all significant factors affecting the loss of signal power in a given situation may often be infeasible. In this paper, we experimentally investigate the influence of deep-indoor features such as indoor depth, indoor distance and distance to the closest tunnel corridor and the effect on received power using NB-IoT. We describe a measurement campaign performed in a system of long underground tunnels, and we analyse linear regression models involving the engineered features. We show that the current empirical models for NB-IoT signal attenuation are inaccurate in a deep-indoor scenario. We observe that 1) indoor distance and penetration depth do not explain the signal attenuation well and increase the error of the prediction by 2-12 dB using existing models, and 2) a promising feature of average distance to the nearest corridor is identified.
|Title of host publication||Proceedings of 2020 IEEE Global Communications Conference|
|Number of pages||6|
|Publication date||Dec 2020|
|Publication status||Published - Dec 2020|
|Event||2020 IEEE Global Communications Conference - Virtual, Taipei, Taipei, Taiwan, Province of China|
Duration: 7 Dec 2020 → 11 Dec 2020
|Conference||2020 IEEE Global Communications Conference|
|Country/Territory||Taiwan, Province of China|
|Period||07/12/2020 → 11/12/2020|
|Sponsor||6G Office, Chunghwa Telecom Co. Ltd., Foxconn, Huawei, MediaTek|
|Series||2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings|
Bibliographical noteFunding Information:
ACKNOWLEDGEMENT This work was partially supported by Innovation Fund Denmark through the Eureka Turbo project IoT Watch4Life.
© 2020 IEEE.
- Signal attenuation