LPWAN Coverage Assessment Planning without Explicit Knowledge of Base Station Locations

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU141341" target="_blank" >RIV/00216305:26220/22:PU141341 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/9507528" target="_blank" >https://ieeexplore.ieee.org/document/9507528</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/JIOT.2021.3102694" target="_blank" >10.1109/JIOT.2021.3102694</a>

Result language

angličtina

Original language name

LPWAN Coverage Assessment Planning without Explicit Knowledge of Base Station Locations

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20203 - Telecommunications

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Internet of Things Journal

ISSN

2327-4662

e-ISSN

—

Volume of the periodical

9

Issue of the periodical within the volume

6

Country of publishing house

US - UNITED STATES

Number of pages

19

Pages from-to

4031-4050

UT code for WoS article

000766683600007

EID of the result in the Scopus database

2-s2.0-85112221686