A ML-based Spectrum Sharing Technique for Time-Sensitive Applications in Industrial Scenarios

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Industry 4.0, driven by enhanced connectivity by
wireless technologies such as 5G and Wi-Fi 6, fosters flexible
industrial scenarios for high-yield production and services. Private
5G networks and 802.11ax networks in unlicensed spectrum offer very unique opportunities, however existing techniques limit the flexibility needed to serve diverse industrial use cases. In order to address a subset of these challenges, this paper offers a solution for time-sensitive application use cases. A new technique is proposed to enable data-driven operations through Machine Learning for technologies sharing unlicensed bands. This enables proportionate spectrum sharing informed by data to improve critical applications performance metrics. The results presented reveal improved performance to serve critical industrial operations, without degrading spectrum utilization.
Original languageEnglish
Title of host publication2023 International Wireless Communications and Mobile Computing (IWCMC)
PublisherIEEE Computer Society
Pages1-6
Publication statusAccepted/In press - 28 Mar 2024
EventIWCMC 2023: The 19th International Wireless Communications and Mobile Computing 2023 - Marrakesh, Morocco
Duration: 19 Jun 202323 Jun 2023
Conference number: 19
https://www.comsoc.org/conferences-events/international-wireless-communications-and-mobile-computing-2023

Conference

ConferenceIWCMC 2023: The 19th International Wireless Communications and Mobile Computing 2023
Abbreviated titleIWCMC 2023
Country/TerritoryMorocco
CityMarrakesh
Period19/06/2323/06/23
Internet address

Keywords

  • 5G
  • 802.11ax
  • Spectrum Sharing
  • Contention Window
  • Time-Sensitive Applications

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