Using LSTM Network for Predicting Radio Mobile Networks’ Behaviors

Sử dụng mạng LSTM để dự báo hành vi mạng thông tin vô tuyến di động

  • Cuong Pham-Quoc
  • Tuan Tung-Anh
  • Chien Tang-Tan Faculty of Computerand Electronics Engineering, Vietnam – Korea University ofInformation and Communication Technology, The University ofDanang, Vietnam
Keywords: Long-Short Term Memory, predicting, behavior, radio mobile network, data

Abstract

Breakthroughs in artificial intelligence, machine learning and deep learning with great recent achievements have been strongly impacting the mobile communication industry. The traditional method of mobile network management and operation has been shifting toward automation and proactive monitoring. Forecasting radio mobile networks’ behaviors in coexisting multi-layer technology mobile networks for improving resource allocation efficiency and optimizing network’s key performance indicators becomes a critical task. The use of a Long-Short Term Memory (LSTM) network for predicting radio networks’ behaviors based on real statistical data from operational support systems is suggested in this research. The promising results show the potential of our approach. The prediction results can help mobile network operators leverage networks’ operating performance.

Author Biographies

Cuong Pham-Quoc

Cuong Pham-Quoc1, Tuan Tang-Anh2, and Chien Tang-Tan3
1 MobiFone Corporation, Hanoi, Vietnam
cuong.phamquoc@mobifone.vn
2 Faculty of Electronics and Telecommunication Engineering, University of Science
and Technology, The University of Danang, Danang, Vietnam
tanganhtuan@dut.udn.vn
3 Faculty of Computer and Electronics Engineering, Vietnam – Korea University of
Information and Communication Technology, The University of Danang, Danang,
Vietnam
ttchien@ac.udn.vn

Tuan Tung-Anh

Received his B.E. degree in electronic and communication from
Danang University of Science and Technology, Vietnam, in 2013 and his Ph.D. degree
at University of Leeds, United Kingdom, in 2019. His research interests include SDN,
security, intrusion detection, machine learning and deep learning.

Chien Tang-Tan, Faculty of Computerand Electronics Engineering, Vietnam – Korea University ofInformation and Communication Technology, The University ofDanang, Vietnam

Received his Bachelor degree in Physics - Electronics from the
University of Science, Ho Chi Minh City,
Vietnam, in 1979. He joined the Department of Electronic and Telecommunication Engineering, the University of Danang,
University of Science and Technology. In
2003, he received his Ph.D. Eng. degree
in Telecommunications Engineering from Hanoi University of
Technology, Vietnam. He was promoted to Associate Professor in
2010. He is currently senior lecturer at the Faculty of Computer
and Electronics Engineering, Vietnam – Korea University of
Information and Communication Technology, The University of
Danang, Vietnam. His research interests include electromagnetic
compatibility (EMC) and signal processing.

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Published
2023-06-30