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| Paper Abstract and Keywords | ||
| Presentation | 2022-02-24 10:05 Study on Bandwidth usage Reduction by Traffic Prediction Using Transfer Learning in Satellite Communication Systems Kazumasab Tamada, Yuichi Kawamoto, Nei Kato (Tohoku Univ.)  SAT2021-54 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Recently, Internet traffic has been increasing owing to the widespread use of teleworking and flat-rate video distribution services. Such enormous traffic is also expected to transmit over the satellite communications lines of the Beyond 5G backhaul network and the fluctuation patterns will become more diversified. The resources of satellite communication are scarcer than terrestrial communication. Therefore, this research focuses on efficient satellite network resource operation. Traffic forecasting is one of the promising approaches for efficient resource allocation. There are several methods for traffic prediction of terrestrial communication using machine learning. However, there are no literatures focusing on traffic prediction using ML over satellite communication. This is challenging due to high bandwidth consumption by the existing prediction methods over limited satellite bandwidth that can lower bandwidth usage for users. Therefore, this paper proposes a traffic prediction method that uses transfer learning to reduce the bandwidth usage by the proposed approach. Furthermore, we perform simulations to compare the prediction accuracy of the proposed method with the conventional approach to verify the performance of the proposed approach. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Satellite communication / Machine learning / Traffic prediction / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 379, SAT2021-54, pp. 7-12, Feb. 2022. | |
| Paper # | SAT2021-54 | |
| Date of Issue | 2022-02-17 (SAT) | |
| 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 | SAT2021-54 |
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| Conference Information | |
| Committee | SAT SANE |
| Conference Date | 2022-02-24 - 2022-02-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Satellite technology, etc. |
| Paper Information | |
| Registration To | SAT |
| Conference Code | 2022-02-SAT-SANE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Study on Bandwidth usage Reduction by Traffic Prediction Using Transfer Learning in Satellite Communication Systems |
| Sub Title (in English) | |
| Keyword(1) | Satellite communication |
| Keyword(2) | Machine learning |
| Keyword(3) | Traffic prediction |
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| 1st Author's Name | Kazumasab Tamada |
| 1st Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 2nd Author's Name | Yuichi Kawamoto |
| 2nd Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 3rd Author's Name | Nei Kato |
| 3rd Author's Affiliation | Tohoku University (Tohoku Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-02-24 10:05:00 |
| Presentation Time | 25 minutes |
| Registration for | SAT |
| Paper # | SAT2021-54 |
| Volume (vol) | vol.121 |
| Number (no) | no.379 |
| Page | pp.7-12 |
| #Pages | 6 |
| Date of Issue | 2022-02-17 (SAT) |
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