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Grant-free Radio Access IoT Networks:Scalability Analysis in Coexistence Scenarios
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab). (COS)ORCID iD: 0000-0003-4006-5848
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab). (COS)ORCID iD: 0000-0003-0125-2202
Ericsson AB, Stockholm, Sweden.
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).ORCID iD: 0000-0003-0525-4491
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

IoT networks with grant-free radio access, likeSigFox and LoRa, offer low-cost durable communications overunlicensed band. These networks are becoming more and morepopular due to the ever-increasing need for ultra durable, interms of battery lifetime, IoT networks. Most studies evaluatethe system performance assuming single radio access technologydeployment. In this paper, we study the impact of coexistingcompeting radio access technologies on the system performance.Considering K technologies, defined by time and frequencyactivity factors, bandwidth, and power, which share a set of radioresources, we derive closed-form expressions for the successfultransmission probability, expected battery lifetime, and experienceddelay as a function of distance to the serving access point.Our analytical model, which is validated by simulation results,provides a tool to evaluate the coexistence scenarios and analyzehow introduction of a new coexisting technology may degrade thesystem performance in terms of success probability and batterylifetime. We further investigate solutions in which this destructiveeffect could be compensated, e.g., by densifying the network toa certain extent and utilizing joint reception.

Place, publisher, year, edition, pages
2018.
Keywords [en]
battery lifetime, IoT, LoRa, LPWA network, interference modelling.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-232215OAI: oai:DiVA.org:kth-232215DiVA, id: diva2:1233085
Conference
IEEE ICC 2018
Note

QC 20180716

Available from: 2018-07-15 Created: 2018-07-15 Last updated: 2018-07-16Bibliographically approved

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fulltext(369 kB)97 downloads
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Type fulltextMimetype application/pdf

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Masoudi, MeysamAzari, AminCavdar, Cicek

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CiteExportLink to record
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  • apa
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