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| Presentation | 2021-01-26 10:00 Channel Selection Method with Multi-Armed Bandit Algorithm for Spectrum Sharing Takashi Imanaka, Mai Ohta, Makoto Taroumaru (Fukuoka Univ.)  SR2020-54 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Recently, there is growing concern about scarcity of frequency resources due to the increase of traffic in wireless communications. A cognitive radio system has attracted attention since in effectively uses limited frequency resources. In order to realize the effective frequency use, a new channel selection method is needed. To share a spectrum with many terminals, it is expected that the channel with the lowest channel occupancy rate is accessed from many terminals. Therefore, we proposed new channel selection method that selects a channel according to a length of transmission packets. In the proposed method, a reinforcement learning is used to select the channel where the length of frequency resource after packet transmissions is short. The performances are evaluated by simulation. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Cognitive radio / Channel selection / Reinforcement learning / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 341, SR2020-54, pp. 39-44, Jan. 2021. | |
| Paper # | SR2020-54 | |
| Date of Issue | 2021-01-18 (SR) | |
| 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 | SR2020-54 |
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| Conference Information | |
| Committee | SR |
| Conference Date | 2021-01-25 - 2021-01-26 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Cognitive Radio, Spectrum Management, Heterogeneous Network, SDN, Machine Learning Application, etc. |
| Paper Information | |
| Registration To | SR |
| Conference Code | 2021-01-SR |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Channel Selection Method with Multi-Armed Bandit Algorithm for Spectrum Sharing |
| Sub Title (in English) | |
| Keyword(1) | Cognitive radio |
| Keyword(2) | Channel selection |
| Keyword(3) | Reinforcement learning |
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| 1st Author's Name | Takashi Imanaka |
| 1st Author's Affiliation | Fukuoka University (Fukuoka Univ.) |
| 2nd Author's Name | Mai Ohta |
| 2nd Author's Affiliation | Fukuoka University (Fukuoka Univ.) |
| 3rd Author's Name | Makoto Taroumaru |
| 3rd Author's Affiliation | Fukuoka University (Fukuoka Univ.) |
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| Speaker | Author-1 |
| Date Time | 2021-01-26 10:00:00 |
| Presentation Time | 25 minutes |
| Registration for | SR |
| Paper # | SR2020-54 |
| Volume (vol) | vol.120 |
| Number (no) | no.341 |
| Page | pp.39-44 |
| #Pages | 6 |
| Date of Issue | 2021-01-18 (SR) |
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