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) |
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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 |
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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 |
6 |
Date of Issue |
2021-12-09 (NS, RCS) |
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