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Analytical Models for Schedule-Based License Assisted Access (LAA) LTE Systems

  • Ekaterina MarkovaEmail author
  • Dmitri Moltchanov
  • Anna Sinitsyna
  • Daria Ivanova
  • Valeria Filipova
  • Irina Gudkova
  • Konstantin Samouylov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11118)

Abstract

The scarcity of resources available for commercial wireless access systems below 6 GHz coupled with constantly increasing traffic demands from the mobile users force network operators to seek additional spectrum. In addition to moving upper in the frequency band and occupying millimeter wave band with 3GPP New Radio access technology the set of solutions also includes implementing commercial LTE systems in unlicensed bands including 2.4 GHz and 5.1 GHz that are currently occupied by Wi-Fi. This technology, known as License Assisted Access (LAA), has recently received considerable attention within the 3GPP community. One of the solutions to provide fair division of air interface resources between competing technologies is to use schedule-based access, where LAA access point is in full control of shared medium and may dynamically schedule allocations to LTE and Wi-Fi traffic. The fine tuning of LAA technology requires careful understanding of various trade-offs and dependencies involved in Wi-Fi and LTE coexistence. In this paper, using the tools of the queuing theory we formulate and solve several analytical models targeting different implementation strategies of schedule-based LAA systems and traffic types of end users. We derive relevant performance characteristics including the session drop probabilities, probability that the session accepted to the system is drop before its service completion and average resource utilization of the system.

Keywords

LTE 4G LAA License-assisted access Analytical models 

Notes

Acknowledgement

The publication has been prepared with the support of the “RUDN University Program 5-100” and funded by RFBR according to the research projects No. 18-37-00231 and No. 16-07-00766.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Ekaterina Markova
    • 1
    Email author
  • Dmitri Moltchanov
    • 1
    • 2
  • Anna Sinitsyna
    • 1
  • Daria Ivanova
    • 1
  • Valeria Filipova
    • 1
  • Irina Gudkova
    • 1
    • 3
  • Konstantin Samouylov
    • 1
    • 3
  1. 1.Department of Applied Probability and InformaticsPeoples’ Friendship University of Russia (RUDN University)MoscowRussia
  2. 2.Department of Electronics and Communications EngineeringTampere University of TechnologyTampereFinland
  3. 3.Institute of Informatics Problems, Federal Research Center“Computer Science and Control” of the Russian Academy of SciencesMoscowRussia

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