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A dataset to evaluate IEEE 802.15.4g sun for dependable low-power wireless communications in industrial scenarios

Authors :
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció
Universitat Politècnica de Catalunya. GRIC - Grup de Recerca i Innovació de la Construcció
Tuset Peiro, Pere
Cuerva Contreras, Eva
Egusquiza Estévez, Eduard
Vilajosana Guillén, Xavier
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció
Universitat Politècnica de Catalunya. GRIC - Grup de Recerca i Innovació de la Construcció
Tuset Peiro, Pere
Cuerva Contreras, Eva
Egusquiza Estévez, Eduard
Vilajosana Guillén, Xavier
Publication Year :
2020

Abstract

This article presents a dataset obtained from the deployment of an IEEE 802.15.4g SUN (Smart Utility Network) single-hop network (11 nodes) in a large industrial scenario (110,044 m 2 ) for a long period of time (99 days). The dataset contains ~11 M entries with RSSI (Received Signal Strength Indicator), CCA (Clear Channel Assessment), and PDR (Packet Delivery Ratio) values. The analyzed results show a high variability in the average RSSI (i.e., between -82.1 dBm and -101.7 dBm) and CCA (i.e., between -111.2 dBm and -119.9 dBm) values, which is caused by the effects of multi-path propagation and external interference. Despite being above the sensitivity limit for each modulation, these values result in poor average PDR values (i.e., from 65.9% to 87.4%), indicating that additional schemes are needed to meet the link reliability requirements of industrial applications. Hence, the presented dataset will allow researchers and practitioners to propose novel mechanisms and evaluate their performance using realistic conditions, enabling the dependability vision of the RAW (Reliable and Available Wireless) WG (Working Group) at the IETF (Internet Engineering Task Force).<br />Peer Reviewed<br />Postprint (published version)

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1238016589
Document Type :
Electronic Resource