A Sensitivity Analysis on the Potential of 5G Channel Quality Prediction

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Abstract

With increasing network complexity, intelligent mechanisms to efficiently achieve the required quality of service of wireless-enabled applications are being developed, especially for industrial environments due to the onset of the fourth industrial revolution. In this paper, the potential benefits of wireless channel quality prediction for two of the three major use cases supported by 5G viz. enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low Latency Communication (URLLC) are quantified in an industrial indoor environment through simulations. Our analysis shows that the ability to perform perfect prediction improves the 10th user throughput percentile by up to 125% for eMBB use case and decreases the 90th resource utilization percentile by up to 37% for URLLC use case. Furthermore, the maximum tolerable prediction inaccuracy is found to be up to 5 dB and 0.35 dB for eMBB and URLLC use cases, respectively.

Original languageEnglish
Title of host publication2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)
Place of PublicationPiscataway, NJ
PublisherIEEE
ISBN (Electronic)978-1-7281-8964-2
ISBN (Print)978-1-7281-8965-9
DOIs
Publication statusPublished - 15 Jun 2021
EventIEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Online Event
Duration: 25 Apr 202128 Apr 2021
Conference number: 93
https://events.vtsociety.org/vtc2021-spring/

Publication series

NameIEEE Vehicular Technology Conference, VTC
PublisherIEEE
Volume2021
ISSN (Print)1550-2252
ISSN (Electronic)2577-2465

Conference

ConferenceIEEE 93rd Vehicular Technology Conference, VTC 2021-Spring
Abbreviated titleVTC2021-Spring
CityOnline Event
Period25/04/2128/04/21
Internet address

Keywords

  • 5G
  • Factories of the Future
  • Industrial IoT
  • Networking

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