Open AccessOn the application of support vector machines to the prediction of propagation losses at 169 MHz for smart metering applications
Author(s) -
Uccellari Martino,
Facchini Francesca,
Sola Matteo,
Sirignano Emilio,
Vitetta Giorgio M.,
Barbieri Andrea,
Tondelli Stefano
Publication year - 2018
Publication title -
iet microwaves, antennas and propagation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.555
H-Index - 69
eISSN - 1751-8733
pISSN - 1751-8725
DOI - 10.1049/iet-map.2017.0364
Subject(s) - metering mode , support vector machine , transmission (telecommunications) , computer science , wireless , software , radio propagation , field (mathematics) , set (abstract data type) , electronic engineering , signal strength , data transmission , software defined radio , computer engineering , real time computing , machine learning , data mining , engineering , computer hardware , telecommunications , mathematics , mechanical engineering , pure mathematics , programming language
Recently, the need of deploying new wireless networks for smart gas metering has raised the problem of radio planning in the 169 MHz band. Unluckily, software tools commonly adopted for radio planning in cellular communication systems cannot be employed to solve this problem because of the substantially lower transmission frequencies characterising this application. In this study, a novel data‐centric solution, based on the use of support vector machine techniques for classification and regression, is illustrated. The proposed method requires the availability of a limited set of received signal strength measurements and the knowledge of a three‐dimensional map of the propagation environment of interest and generates both an estimate of the coverage area and a prediction of the field strength within it. Various numerical results show that the proposed method is able to achieve good accuracy at the price of an acceptable computational cost and of a limited effort for the acquisition of measurements in the considered environments.