LPWAN coverage assessment planning without explicit knowledge of base station locations
|Author:||Stusek, Martin1,2; Moltchanov, Dmitri2; Masek, Pavel1;|
1Brno University of Technology, Faculty of Electrical Engineering and Communications, Dept. of Telecommunications, Technicka 12, 61600 Brno, Czech Republic
2Tampere University, Unit of Electrical Engineering, Korkeakoulunkatu 7, 33720 Tampere, Finland
3University of Oulu, Center for Wireless Communications, Pentti Kaiteran katu 1, 90570 Oulu, Finland
4ITMO University, Faculty of Software Engineering and Computer Systems, Kronverkskiy Prospekt, 49, St.Petersburg, Russia
5Vodafone Czech Republic a.s., Namesti Junkovych 2808/2, 15500 Prague, Czech Republic
|Online Access:||PDF Full Text (PDF, 8.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021082744481
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2021-08-27
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.
IEEE internet of things journal
|Pages:||1 - 19|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
For this research, the infrastructure of the SIX Center was used. This article is based upon the support of international mobility project MeMoV, No. CZ.02.2.69/0.0/0.0/16 027/00083710 funded by the European Union, Ministry of Education, Youth and Sports, Czech Republic, and Brno University of Technology. The work of K.Mikhaylov has been supported by the Academy of Finland 6G Flagship (grant 318927).
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.