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A Model for 5G Millimeter Wave Service Rate Abstraction

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Distributed Computer and Communication Networks (DCCN 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1748))

Abstract

An accurate channel abstraction is an important part of solving resource allocation problems in 5G networks. The purpose of this work is to present a channel abstraction model that takes into account changes in total cell capacity over time and does not require complex simulation. We analyze the cell capacity, taking into account the 3GPP standards. Based on the obtained values, we propose a model based on the first-order autoregression method. The numerical results show that the suggested method provides an accurate approximation of the total cell rate. The obtained results can be used in applied research in 5G wireless networks.

The research was funded by the Russian Science Foundation, project No22-29-00222 (https://rscf.ru/en/project/22-29-00222).

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Author information

Authors and Affiliations

  1. Higher School of Economics (HSE University), 20 Myasnitskaya St., Moscow, 101000, Russian Federation

    Vladislav Prosvirov & Emil Khayrov

  2. Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

    Evgeny Mokrov

Authors
  1. Vladislav Prosvirov
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  2. Emil Khayrov
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  3. Evgeny Mokrov
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Corresponding author

Correspondence to Vladislav Prosvirov .

Editor information

Editors and Affiliations

  1. V. A. Trapeznikov Institute of Control Sciences of RAS, Moscow, Russia

    Vladimir M. Vishnevskiy

  2. RUDN University, Moscow, Russia

    Konstantin E. Samouylov

  3. V. A. Trapeznikov Institute of Control Sciences of RAS, Moscow, Russia

    Dmitry V. Kozyrev

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Prosvirov, V., Khayrov, E., Mokrov, E. (2023). A Model for 5G Millimeter Wave Service Rate Abstraction. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds) Distributed Computer and Communication Networks. DCCN 2022. Communications in Computer and Information Science, vol 1748. Springer, Cham. https://doi.org/10.1007/978-3-031-30648-8_14

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  • DOI: https://doi.org/10.1007/978-3-031-30648-8_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30647-1

  • Online ISBN: 978-3-031-30648-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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