Systems and Means of Informatics
2021, Volume 31, Issue 3, pp 135-143
AN EXAMPLE OF NEURAL NETWORK USAGE FOR ASSIGNING A MODULATION-CODE SCHEME TO A 5G BASE STATION SCHEDULER
- E. V. Bobrikova
- A. A. Platonova
- Yu. V. Gaidamaka
- S. Ya. Shorgin
Abstract
The article proposes a method for assigning a modulation-code scheme by a base station scheduler based on predicting the value of the signal-to- interference ratio on the mobile user's equipment at the next time slot from a sequence of known values of this ratio in the past. For prediction, a model of a single-layer neural network is built in the work, by the example of which a machine learning process is shown for solving a multiparametric optimization problem using the stochastic gradient method. The trained neural network for the predicted value of the signal/interference ratio allows the scheduler to correctly select the modulation-code scheme for the user, thereby ensuring the level of quality of data transmission in the radio channel required for the provision of the service.
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[+] About this article
Title
AN EXAMPLE OF NEURAL NETWORK USAGE FOR ASSIGNING A MODULATION-CODE SCHEME TO A 5G BASE STATION SCHEDULER
Journal
Systems and Means of Informatics
Volume 31, Issue 3, pp 135-143
Cover Date
2021-11-10
DOI
10.14357/08696527210312
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
SINR; machine learning; neural network
Authors
E. V. Bobrikova  , A. A. Platonova , Yu. V. Gaidamaka ,  , and S. Ya. Shorgin
Author Affiliations
Peoples' Friendship University of Russia (RUDN University), 6 Miklukho- Maklaya Str., Moscow 117198, Russian Federation
Federal Research Center "Computer Science and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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