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Paper Abstract and Keywords
Presentation 2026-03-06 10:20
Dynamic Resource Control for 5G Network Slicing using Deep Learning-based Traffic Prediction: A Study on Proposal and Implementation
Miyu Yoshimura, Shuya Abe (FUT) NS2025-314
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, network slicing has been introduced in 5G mobile networks to satisfy diverse communication requirements. However, static resource allocation faces challenges in efficient operation against fluctuating traffic volumes. This paper proposes a dynamic resource control method for 5G slicing based on traffic prediction using a Gated Recurrent Unit and investigates its implementation using open-source software. As a preliminary study toward full-scale implementation, we evaluated the prediction performance using the Milan real-world traffic dataset. The results demonstrated a high prediction accuracy, achieving a coefficient of determination $R^2 = 0.8563$ and a Weighted Absolute Percentage Error of $19.85%$. Furthermore, we constructed an experimental environment leveraging free5GC and UERANSIM to confirm the feasibility of the proposed dynamic control architecture. This study establishes a technical foundation for realizing efficient dynamic resource allocation by capturing future load fluctuations in advance.
Keyword (in Japanese) (See Japanese page) 
(in English) Mobile Network / Network Slicing / GRU / OSS / Resource Provisioning / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 385, NS2025-314, pp. 545-550, March 2026.
Paper # NS2025-314 
Date of Issue 2026-02-25 (NS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NS2025-314

Conference Information
Committee IN NS  
Conference Date 2026-03-04 - 2026-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa-Ken Shichoson Jichi Kaikan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To NS 
Conference Code 2026-03-IN-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Dynamic Resource Control for 5G Network Slicing using Deep Learning-based Traffic Prediction: A Study on Proposal and Implementation 
Sub Title (in English)  
Keyword(1) Mobile Network  
Keyword(2) Network Slicing  
Keyword(3) GRU  
Keyword(4) OSS  
Keyword(5) Resource Provisioning  
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1st Author's Name Miyu Yoshimura  
1st Author's Affiliation Fukui University of Technology (FUT)
2nd Author's Name Shuya Abe  
2nd Author's Affiliation Fukui University of Technology (FUT)
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Speaker Author-1 
Date Time 2026-03-06 10:20:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2025-314 
Volume (vol) vol.125 
Number (no) no.385 
Page pp.545-550 
#Pages 6 
Date of Issue 2026-02-25 (NS) 

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