Publication detail

Towards 5G Networks Optimization through Machine Learning-aided Processing Large Datasets

YOUNESIAN, E. HOŠEK, J.

Original Title

Towards 5G Networks Optimization through Machine Learning-aided Processing Large Datasets

Type

conference paper

Language

English

Original Abstract

This paper presents a novel approach for optimizing 5G networks through the use of machine learning techniques for processing large datasets. With the increasing demand for high-speed and low-latency communications, 5G networks have emerged as a promising solution. However, the optimization of these networks remains a challenge due to the complexity of the systems and the vast amount of data generated by them. To address this issue, we propose a framework that utilizes data preprocessing in time series data to analyze large datasets and extract useful information. It can be used to optimize various aspects of the 5G network. Specifically, we present results of implementing seasonal decomposition of time series which is one of the techniques in time series forecasting. This preprocessed data will be implemented to time series machine learning models to predict the future delay between routers and finally propose the best available route. Overall, our work presents a valuable contribution to the field of 5G network optimization and highlights the potential of machine learning techniques in this domain.

Keywords

Machine learning, Time series forecasting, Data preprocessing, Beyond 5G networks, Network slicing

Authors

YOUNESIAN, E.; HOŠEK, J.

Released

25. 4. 2023

Publisher

Brno University of Technology, Faculty of Electrical Engineering and Communication

Location

Brno

ISBN

978-80-214-6153-6

Book

Proceedings I of the 29th year Conference Student EEICT 2023 General papers

Edition

1

Pages from

369

Pages to

373

Pages count

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf

BibTex

@inproceedings{BUT183352,
  author="Elham {Younesian} and Jiří {Hošek}",
  title="Towards 5G Networks Optimization through Machine Learning-aided Processing Large Datasets",
  booktitle="Proceedings I of the 29th year Conference Student EEICT 2023 General papers",
  year="2023",
  series="1",
  pages="369--373",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6153-6",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf"
}