LPWAN Coverage Assessment Planning without Explicit Knowledge of Base Station Locations

LPWAN Coverage Assessment Planning without Explicit Knowledge of Base Station Locations

Článek WoS

An assessment of radio network coverage, usually in the form of a measurement campaign, is essential for multi-base-station (multi-BS) network deployment and maintenance. It can be conducted by a network operator or its served consumers. However, the number of measurement points and their locations may not be known in advance for an efficient and accurate evaluation. The main goal of this study is to propose a new methodology for understanding the selection of measurement points during coverage and signal quality assessment. It is particularly tailored to multi-BS low-power wide-area network (LPWAN) deployments without explicit knowledge of BS locations. To this aim, we first conduct a large-scale measurement campaign for three popular LPWAN technologies, namely, NB-IoT, Sigfox, and LoRaWAN. Utilizing this baseline data, we develop a procedure for identifying the minimum set of measurement points for the coverage assessment with a given accuracy as well as study which interpolation algorithms produce the lowest approximation error. Our results demonstrate that a random choice of measurement points is on par with their deterministic selection. Out of the candidate interpolation algorithms, Kriging method offers attractive performance in terms of the absolute error for NB-IoT deployments. By contrast, for Sigfox and LoRaWAN infrastructures, less complex techniques, such as Natural-neighbor, Linear interpolation, or Inverse-Distance Weighting, can achieve comparable (and occasionally even better) accuracy levels.

An assessment of radio network coverage, usually in the form of a measurement campaign, is essential for multi-base-station (multi-BS) network deployment and maintenance. It can be conducted by a network operator or its served consumers. However, the number of measurement points and their locations may not be known in advance for an efficient and accurate evaluation. The main goal of this study is to propose a new methodology for understanding the selection of measurement points during coverage and signal quality assessment. It is particularly tailored to multi-BS low-power wide-area network (LPWAN) deployments without explicit knowledge of BS locations. To this aim, we first conduct a large-scale measurement campaign for three popular LPWAN technologies, namely, NB-IoT, Sigfox, and LoRaWAN. Utilizing this baseline data, we develop a procedure for identifying the minimum set of measurement points for the coverage assessment with a given accuracy as well as study which interpolation algorithms produce the lowest approximation error. Our results demonstrate that a random choice of measurement points is on par with their deterministic selection. Out of the candidate interpolation algorithms, Kriging method offers attractive performance in terms of the absolute error for NB-IoT deployments. By contrast, for Sigfox and LoRaWAN infrastructures, less complex techniques, such as Natural-neighbor, Linear interpolation, or Inverse-Distance Weighting, can achieve comparable (and occasionally even better) accuracy levels.

Interpolation; Urban areas; Phase measurement; Measurement uncertainty; Internet of Things; Wireless communication; Weight measurement

Interpolation; Urban areas; Phase measurement; Measurement uncertainty; Internet of Things; Wireless communication; Weight measurement

ŠTŮSEK, M.; MOLTCHANOV, D.; MAŠEK, P.; MIKHAYLOV, K.; HOŠEK, J.; ANDREEV, S.; KUCHERYAVY, E.; KUSTAREV, P.; ZEMAN, O.; ROUBÍČEK, M.

2022

15.03.2022

IEEE Internet of Things Journal

2327-4662

IEEE Internet of Things Journal

9

6

Spojené státy americké

4031

4050

19

https://ieeexplore.ieee.org/document/9507528