Analytical modeling and design of energy efficient class-selection for long range wide area networks

Wun Ci Su, Tzu I. Wu, Pei Rong Li, Kai-Ten Feng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Long range wide area networks (LoRaWAN) is one of the novel specification for the applications of Internet-of-Things. Recent research focused on the propagation model and coverage discussion based on experimental measurement. In this paper, power- class analytical model is firstly proposed to model the operations of LoRaWAN end-devices for throughput and power consumption. Based on this model, the energy efficient class-selection algorithm (EECA) is proposed to achieve the optimal energy efficiency with the consideration of power consumption on end-devices by the suitable class selection scheme. A system level simulation has been conducted for performance evaluation. The simulation results provide the guideline for system parameters configuration and class selection on each end-devices under different scenarios.

Original languageEnglish
Title of host publication2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728112176
DOIs
StatePublished - 1 Apr 2019
Event89th IEEE Vehicular Technology Conference, VTC Spring 2019 - Kuala Lumpur, Malaysia
Duration: 28 Apr 20191 May 2019

Publication series

NameIEEE Vehicular Technology Conference
Volume2019-April
ISSN (Print)1550-2252

Conference

Conference89th IEEE Vehicular Technology Conference, VTC Spring 2019
CountryMalaysia
CityKuala Lumpur
Period28/04/191/05/19

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