University of Oulu

S. P. Sone, J. Lehtomäki, Z. Khan and K. Umebayashi, "Forecasting Wireless Network Traffic and Channel Utilization Using Real Network/Physical layer Data," 2021 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), 2021, pp. 31-36, doi: 10.1109/EuCNC/6GSummit51104.2021.9482498

Forecasting wireless network traffic and channel utilization using real network/physical layer data

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Author: Sone, Su Pyae1; Lehtomäki, Janne1; Khan, Zaheer1;
Organizations: 1Centre for Wireless Communications (CWC), University of Oulu, Finland
2Tokyo University of Agriculture and Technology, Japan
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-10-21


Prediction of wireless network parameters, such as traffic (TU) and channel utilization (CU) data, can help in proactive resource allocation to handle the increasing amount of devices in an enterprise network. In this work, we examined the medium-to-long-scale forecasting of TU and CU data collected from an enterprise network using classical methods, such as Holt-Winters, Seasonal ARIMA (SARIMA), and machine learning methods, such as long short-term memory (LSTM) and gated recurrent unit (GRU). We also improved the performance of conventional LSTM and GRU for time series forecasting by proposing features-like grid training data structure which uses older historical data as features. The wireless network time series pre-processing methods and the verification methods are presented as time series analysis steps. The model hyper-parameters selections process and the comparison of different forecasting models are also provided. This work has proven that physical layer data has more predictive power in time series forecasting aspect with all forecasting models.

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Series: European Conference on Networks and Communications
ISSN: 2475-6490
ISSN-E: 2575-4912
ISSN-L: 2475-6490
ISBN: 978-1-6654-1526-2
ISBN Print: 978-1-6654-3021-0
Pages: 31 - 36
Article number: 9482498
DOI: 10.1109/EuCNC/6GSummit51104.2021.9482498
Host publication: Joint 30th European Conference on Networks and Communications and 3rd 6G Summit, EuCNC/6G Summit 2021
Conference: Joint European Conference on Networks and Communications & 6G Summit
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work is supported by the Infotech Oulu, Academy of Finland 6Genesis Flagship (grant no. 318927), and the European Commission in the framework of the H2020-EUJ- 02-2018 project 5GEnhance (Grant agreement no. 815056), by "Strategic Information and Communications R&D Promotion Programme (SCOPE)" of Ministry of Internal Affairs and Communications (MIC) of Japan (Grant no. JPJ000595).
EU Grant Number: (815056) 5G-Enhance - 5G Enhanced Mobile Broadband Access Networks in Crowded Environments
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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