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Using Neural Networks for Channel Quality Prediction in Wireless 5G Networks

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Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13766 ))

Abstract

The article proposes a method for assigning a modulation coding scheme (MCS) by a base station (BS) scheduler on an unmanned aerial vehicle (UAV), based on predicting the value of the signal-to-interference-to-noise ratio (SINR) on the mobile user equipment (UE) at the next time slot from a sequence of known values of this ratio in the past. Prediction is performed using machine learning. For this, a neural network was built and applied to solve the problem of multi-parameter optimization using the stochastic gradient method. The trained neural network for the predicted SINR value allows the scheduler to select the modulation-code scheme correctly, thereby ensuring the level of data transmission quality in the radio channel necessary to provide the service.

The reported study was funded by RSF, project number 22-29-00694, https://rscf.ru/en/project/22-29-00694.

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Author information

Authors and Affiliations

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

    Ekaterina Bobrikova, Anna Platonova, Ekaterina Medvedeva & Yu. V. Gaidamaka

  2. Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences (FRC CSC RAS), 44-2 Vavilov Street, Moscow, 119333, Russian Federation

    Ekaterina Medvedeva, Yu. V. Gaidamaka & Sergey Shorgin

Authors
  1. Ekaterina Bobrikova
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  2. Anna Platonova
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  3. Ekaterina Medvedeva
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  4. Yu. V. Gaidamaka
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  5. Sergey Shorgin
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Corresponding author

Correspondence to Anna Platonova .

Editor information

Editors and Affiliations

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

    Vladimir M. Vishnevskiy

  2. Peoples' Friendship University of Russia, Moscow, Russia

    Konstantin E. Samouylov

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

    Dmitry V. Kozyrev

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Bobrikova, E., Platonova, A., Medvedeva, E., Gaidamaka, Y.V., Shorgin, S. (2022). Using Neural Networks for Channel Quality Prediction in Wireless 5G Networks. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds) Distributed Computer and Communication Networks: Control, Computation, Communications. DCCN 2022. Lecture Notes in Computer Science, vol 13766 . Springer, Cham. https://doi.org/10.1007/978-3-031-23207-7_11

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  • DOI: https://doi.org/10.1007/978-3-031-23207-7_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23206-0

  • Online ISBN: 978-3-031-23207-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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