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Paper Abstract and Keywords
Presentation 2019-11-26 10:30
[Poster Presentation] Slice Admission Control Scheme using the Ensemble Learning Method in 5G RAN Slicing Environments
Seungil Moon, Haruhisa Hirayama, Yu Tsukamoto, Shinobu Nanba, Kosuke Nishimura (KDDI Research Inc.)
Abstract (in Japanese) (See Japanese page) 
(in English) Network slicing allows splitting a common shared network across multiple logical networks. It configured to meet the specific service requirements of 5G network systems. Recently, research on applying machine learning for efficient slice resource management and slice admission control in 5G RAN slicing environments has been discussed. But, the existing DRL-based admission control scheme has a problem that it takes long training time to gain significant performance. In this paper, we propose a slice admission control scheme using the ensemble learning method to reduce learning time and improve performance in 5G RAN slicing environments. The ML Model Selector of the Ensemble Method Agent improves the probability of selecting a better model by updating the weight according to the performance of each model (Approximation Framework and DRL Framework) for efficient learning model selection. Through the Ensemble Learning method, it analyzes the performance result of both frameworks then updates the weight for choosing the better model after comparing. The controller selects the ML model base on the probability with weight. Our evaluation result shows that the benefits of the proposed ensemble learning method can be obtained by comparing existing types of learning methods.
Keyword (in Japanese) (See Japanese page) 
(in English) 5G / RAN Slicing / Admission Control / Radio Resource Management / Machine Learning / / /  
Reference Info. IEICE Tech. Rep.
Paper #  
Date of Issue  
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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Conference Information
Committee RISING  
Conference Date 2019-11-26 - 2019-11-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukutake Learning Theater, Hongo Campus, Univ. Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Researches on Super-Intelligent Networking, etc. 
Paper Information
Registration To RISING 
Conference Code 2019-11-RISING 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Slice Admission Control Scheme using the Ensemble Learning Method in 5G RAN Slicing Environments 
Sub Title (in English)  
Keyword(1) 5G  
Keyword(2) RAN Slicing  
Keyword(3) Admission Control  
Keyword(4) Radio Resource Management  
Keyword(5) Machine Learning  
1st Author's Name Seungil Moon  
1st Author's Affiliation KDDI Research Incorporated (KDDI Research Inc.)
2nd Author's Name Haruhisa Hirayama  
2nd Author's Affiliation KDDI Research Incorporated (KDDI Research Inc.)
3rd Author's Name Yu Tsukamoto  
3rd Author's Affiliation KDDI Research Incorporated (KDDI Research Inc.)
4th Author's Name Shinobu Nanba  
4th Author's Affiliation KDDI Research Incorporated (KDDI Research Inc.)
5th Author's Name Kosuke Nishimura  
5th Author's Affiliation KDDI Research Incorporated (KDDI Research Inc.)
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Date Time 2019-11-26 10:30:00 
Presentation Time 50 
Registration for RISING 
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