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A Spatio-temporal Analysis of Cellular-based IoT Networks under Heterogeneous Traffic
IIIT Hyderabad, India.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
Virginia Tech, VA USA.
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-4416-7702
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2021 (English)In: 2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), IEEE , 2021Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we consider a cellular-based Internet of things (IoT) network consisting of IoT devices that can communicate directly with each other in a device-to-device (D2D) fashion as well as send real-time status updates about some underlying physical processes observed by them. We assume that such real-time applications are supported by cellular networks where cellular base stations (BSs) collect status updates over time from a subset of the IoT devices in their vicinity. We characterize two performance metrics: i) the network throughput which quantifies the performance of D2D communications, and ii) the Age of Information which quantifies the performance of the real-time IoT-enabled applications. Concrete analytical results are derived using stochastic geometry by modeling the locations of IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another Independent PPP. Our results provide useful design guidelines on the efficient deployment of future IoT networks that will jointly support D2D communications and several cellular network-enabled real-time applications.

Place, publisher, year, edition, pages
IEEE , 2021.
Series
IEEE Global Communications Conference, ISSN 2334-0983
Keywords [en]
Age of Information; cellular networks; device-to-device communication; IoT networks; stochastic geometry
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-185307DOI: 10.1109/GLOBECOM46510.2021.9685752ISI: 000790747203159ISBN: 9781728181042 (electronic)OAI: oai:DiVA.org:liu-185307DiVA, id: diva2:1662126
Conference
IEEE Global Communications Conference (GLOBECOM), Madrid, SPAIN, dec 07-11, 2021
Note

Funding Agencies|U.S. NSF [CPS-1739642]

Available from: 2022-05-31 Created: 2022-05-31 Last updated: 2022-05-31

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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