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Comparision of LoRa and NB-IoT in Terms of Connectivity
KTH, School of Electrical Engineering and Computer Science (EECS).
2020 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Long Range (LoRa) and Narrow Band Internet of Things (NB-IoT) are twoprotocols widely used in IoT applications. They can provide wireless communicationsbetween devices with low power consumption and wide coverage.Various papers and theses have studied the performance of LoRa and NB-IoT.However, analysis about the comparison between the two protocols has not receivedenough attention. This thesis aims at comparing the performance ofLoRa and NB-IoT in terms of quality of connectivity. The thesis rst introducesthe technical dierences between LoRa and NB-IoT, and analyzes thetheoretical performance. Then, it operates some tests in real-world scenarios,and compares the practical performances of LoRa and NB-IoT based on thetest results. The comparison results show that NB-IoT has a better quality ofconnectivity than LoRa in most of situations.

Abstract [sv]

Long Range (LoRa) och Narrow Band Internet of Things (NB-IoT) är tvåprotokoll som används ofta i IoT-applikationer. De kan tillhandahålla trådlös kommunikation mellan enheter med låg strömförbrukning och bred täckning. Olika artiklar och avhandlingar har studerat prestandan för LoRa och NB-IoT. Analysen om jämförelsen mellan de två protokollen har dock inte fått tillräcklig uppmärksamhet. Denna avhandling syftar till att jämföra prestandan hos LoRa och NB-IoT när det gäller kvaliteten på anslutning. Avhandlingen introducerar först de tekniska skillnaderna mellan LoRa och NB-IoT och analyserar den teoretiska prestationen. Sedan körs det några tester i verkliga scenarier och jämför de praktiska prestationerna för LoRa och NB-IoT baserat på testresultaten. Jämförelsesresultaten visar att NB-IoT har en bättre kvalitet på anslutningen än LoRa i de flesta situationer.

Place, publisher, year, edition, pages
2020. , p. 53
Series
TRITA-EECS-EX ; 2020:23
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-278208OAI: oai:DiVA.org:kth-278208DiVA, id: diva2:1453316
Educational program
Master of Science - Information and Network Engineering
Supervisors
Examiners
Available from: 2020-07-09 Created: 2020-07-09 Last updated: 2022-06-26Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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