skip to main content
10.1145/3479242.3487315acmconferencesArticle/Chapter ViewAbstractPublication PagesmswimConference Proceedingsconference-collections
research-article

Efficient Resource Allocation with Constrained Rate Variability in Cellular Networks

Published:22 November 2021Publication History

ABSTRACT

While LTE networks are known to provide relatively high data rates (on the order of tens of Mbps), these rates exhibit high variability with time. This harms the performance of applications and services requiring stable data rates, such as real-time video streaming, online gaming, XR, etc. 5G emerged as a solution to these kinds of problems. However, strict constant data rates come at the cost of underutilized network resources, which leads to inefficient operation of cellular networks. In this paper, we consider the problem of allocating network resources to cellular users in a way that provides as high a data rate as possible to all users while limiting the rate variation within tight bounds with a given small outage probability. First, we consider the case of static allocation irrespective of channel conditions. Then, we look at the case when resources are allocated dynamically over time. We run simulations on a real trace. Results show that allocating the resources dynamically improves performance over static allocation mechanisms by an additional 10%, and that allowing a slightly higher outage in not complying with the guaranteed data rate further increases the user's throughput.

References

  1. Britta Meixner, Jan Willem Kleinrouweler, and Pablo Cesar. 4G/LTE channel quality reference signal trace data set. In Proc. of ACM MM, 2018. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. 5G radio access. www.ericsson.com/res/docs/whitepapers/wp-5g.pdf, 2016. Ericsson white paper, Uen 284 23--3204 C.Google ScholarGoogle Scholar
  3. M. Bennis, M. Debbah, and H. V. Poor. Ultra-reliable and low-latency wireless communication: Tail, risk, and scale. Proceedings of the IEEE, 106(10), 2018.Google ScholarGoogle Scholar
  4. F. Mehmeti and C. Rosenberg. How expensive is consistency? Performance analysis of consistent rate provisioning to mobile users in cellular networks. IEEE Transactions on Mobile Computing, 18(5), 2019.Google ScholarGoogle ScholarCross RefCross Ref
  5. F. Mehmeti and T. La Porta. Optimizing 5G performance by reallocating unused resources. In Proc. of IEEE ICCCN, 2019.Google ScholarGoogle ScholarCross RefCross Ref
  6. A. Goldsmith. Wireless communications. Cambridge University Press, 2005. Google ScholarGoogle ScholarCross RefCross Ref
  7. G. Ku and J. M. Walsh. Resource allocation and link adaptation in LTE and LTE Advanced: A tutorial. IEEE Communications Surveys & Tutorials, 17(3), 2015.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. ETSI. 5G NR overall description: 3GPP TS 38.300 version 15.3.1 release 15. www.etsi.org, 2018. Technical specification.Google ScholarGoogle Scholar
  9. C. Mehlfuhrer, M. Wrulich, J. Ikuno, D. Bosanska, and M. Rupp. Simulating the Long Term Evolution physical layer. In Proc. of EUSIPCO, 2009.Google ScholarGoogle Scholar
  10. D. Kim, B. C. Jung, H. Lee, D. K. Sung, and H. Yoon. Optimal modulation and coding scheme selection in cellular networks with hybrid-ARQ error control. IEEE Transactions on Wireless Communications, 7(12), 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. S. E. Elayoubi, S. B. Jemaa, Z. Altman, and A. Galindo-Serrano. 5G RAN slicing for verticals: Enablers and challenges. IEEE Comm. Magazine, 57(1), 2019. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Sheldon M. Ross. Stochastic Processes. John Wiley & Sons, 1996.Google ScholarGoogle Scholar
  13. A. Oppenheim and A. Willsky. Signals and systems. Prentice Hall, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. https://zenodo.org/record/1220256#.XiZbo8hKhPY.Google ScholarGoogle Scholar
  15. Bai Cells. Baicells technical training. https://baicells.zendesk.com/hc/en-us/articles/115003137453-WISPAPALOOZA-2017-Technical-Training-Slides, 2017. Tech report.Google ScholarGoogle Scholar
  16. A. Samuylov, D. Moltchanov, R. Kovalchukov, R. Pirmagomedov, Y. Gaidamaka, S. Andreev, Y. Koucheryavy, and K. Samouylov. Characterizing resource allocation trade-offs in 5G NR serving multicast and unicast traffic. IEEE Transactions on Wireless Communications, 19(5), 2020.Google ScholarGoogle ScholarCross RefCross Ref
  17. https://www.synopi.com/bandwidth-required-for-hd-fhd-4k-video/.Google ScholarGoogle Scholar
  18. https://help.netflix.com/en/node/306.Google ScholarGoogle Scholar
  19. Y. Qi, M. Hunukumbure, M. Nekovee, J. Lorca, and V. Sgardoni. Quantifying data rate and bandwidth requirements for immersive 5G experience. In Proc. of IEEE ICC Workshop on 5G RAN Design, 2016.Google ScholarGoogle Scholar
  20. F. Mehmeti and T. La Porta. Admission control for consistent users in next generation cellular networks. In Proc. of IEEE ICC, 2019.Google ScholarGoogle ScholarCross RefCross Ref
  21. F. Mehmeti and C. Rosenberg. Providing consistent rates for backhauling of mobile base stations in public urban transportation. In Proc. of IEEE ICC, 2017.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Efficient Resource Allocation with Constrained Rate Variability in Cellular Networks

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        Q2SWinet '21: Proceedings of the 17th ACM Symposium on QoS and Security for Wireless and Mobile Networks
        November 2021
        143 pages
        ISBN:9781450390804
        DOI:10.1145/3479242

        Copyright © 2021 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 22 November 2021

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate46of131submissions,35%
      • Article Metrics

        • Downloads (Last 12 months)20
        • Downloads (Last 6 weeks)0

        Other Metrics

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader