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Paper Abstract and Keywords
Presentation 2021-12-17 14:05
[Invited Lecture] Performance evaluation on QoS Prediction between Terminals and Access Points Using Convolutional Neural Network
Hiroya Ono, Yuki Sakaue, Satoshi Narikawa (NTT) NS2021-108 RCS2021-191
Abstract (in Japanese) (See Japanese page) 
(in English) Recent mobile terminals have been able to choose from multiple connection options, and optimally accommodating them to each communication resource is an important issue for network carriers to maximize the user quality of experience. In order to dynamically optimize the connection patterns between base stations and terminals, fast and accurate prediction of communication quality for virtual connection patterns is necessary. We have proposed a prediction method using convolutional neural networks (CNN), which is expected to be faster than network simulation and capable of more complex regression than mathematical models. In this paper, we present the performance evaluation results of the proposed method for predicting uplink and downlink throughputs when the system size and the section to be predicted are extended.
Keyword (in Japanese) (See Japanese page) 
(in English) Wireless Access Network / Optimization / Convolutional Neural Network / / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 301, NS2021-108, pp. 59-64, Dec. 2021.
Paper # NS2021-108 
Date of Issue 2021-12-09 (NS, RCS) 
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 NS2021-108 RCS2021-191

Conference Information
Committee RCS NS  
Conference Date 2021-12-16 - 2021-12-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Nara-ken Bunka Kaikan and Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Multi-hop/Relay/Cooperation, Disaster-resistant wireless network, Sensor/Mesh network, Ad-hoc network, D2D/M2M, Wireless network coding, Handover/AP switching/Connected cell control/Load balancing among base stations/Mobile network dynamic reconfiguration, QoS/QoE assurance, Wireless VoIP, IoT, Edge computing, etc. 
Paper Information
Registration To NS 
Conference Code 2021-12-RCS-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance evaluation on QoS Prediction between Terminals and Access Points Using Convolutional Neural Network 
Sub Title (in English)  
Keyword(1) Wireless Access Network  
Keyword(2) Optimization  
Keyword(3) Convolutional Neural Network  
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1st Author's Name Hiroya Ono  
1st Author's Affiliation NTT Corporation (NTT)
2nd Author's Name Yuki Sakaue  
2nd Author's Affiliation NTT Corporation (NTT)
3rd Author's Name Satoshi Narikawa  
3rd Author's Affiliation NTT Corporation (NTT)
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Speaker Author-1 
Date Time 2021-12-17 14:05:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2021-108, RCS2021-191 
Volume (vol) vol.121 
Number (no) no.301(NS), no.302(RCS) 
Page pp.59-64(NS), pp.82-87(RCS) 
#Pages
Date of Issue 2021-12-09 (NS, RCS) 


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