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Impact of Tunable Parameters in NB-IoT Stack onthe Energy Consumption
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-5495-4318
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)ORCID iD: 0000-0002-6723-881X
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)ORCID iD: 0000-0003-4147-9487
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)ORCID iD: 0000-0001-7311-9334
2019 (English)In: Proceedings of Fifteenth Swedish National Computer Networking Workshop (SNCNW), 2019Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies the impact of tunable parametersin the NB-IoT stack on the energy consumption of a user equipment(UE), e.g., a wireless sensor. NB-IoT is designed to enablemassive machine-type communications for UE while providing abattery lifetime of up to 10 years. To save battery power, most oftime the UE is in dormant state and unreachable. Still, duringthe CONNECTED and IDLE state, correct tuning of criticalparameters, like Discontinuous reception (DRX), and extendedDiscontinuous reception (eDRX), respectively, are essential to savebattery power. Moreover, the DRX and eDRX actions relate tovarious parameters which are needed to be tuned in order toachieve a required UE battery lifetime. The objective of thispaper is to observe the influence of an appropriate tuning ofthese parameters to reduce the risk of an early battery drainage

Place, publisher, year, edition, pages
2019.
Keywords [en]
NB-IoT, energy consumption, DRX, eDRX.
National Category
Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-72440OAI: oai:DiVA.org:kau-72440DiVA, id: diva2:1323443
Conference
15th Swedish National Computer Networking Workshop (SNCNW 2019). Luleå, June 4-5, 2019.
Projects
HITS; 4707
Funder
Knowledge FoundationAvailable from: 2019-06-12 Created: 2019-06-12 Last updated: 2019-07-03Bibliographically approved

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Abbas, Muhammad TahirEklund, JohanGrinnemo, Karl-JohanBrunström, Anna

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CiteExportLink to record
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