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| Presentation | 2024-03-15 16:15 Study on Small Cell ON/OFF Control Using Different Frequency Cell Information Takaharu Kobayashi, Takashi Dateki (Fujitsu)  RCS2023-292 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we propose small cell ON/OFF control without using UE position information and information on the proximity relation between UE and small cell, and report the initial study. Concretely, the reinforcement learning model which decides the ON/OFF state of the small cell based on the macro beam number traffic distribution which combines the traffic information with the optimum beam number information of the macro cell was constructed in HetNet (heterogenous network) which consists of the macro cell and the small cell with different frequencies, and performance evaluation was carried out. As a reinforcement learning technique, we used PPO (Proximal Policy Optimization) which is a kind of Actor Critic reinforcement learning. We defined reinforcement learning using geographic traffic information which combines traffic information with location information as a conventional method, and compared it with the proposed method. As the result, it was confirmed that the performance equivalent to the conventional method could be realized even using the proposed method which does not need the position information. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | HetNet / ON/OFF control / Deep Reinforcement Learning / PPO / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 434, RCS2023-292, pp. 176-181, March 2024. | |
| Paper # | RCS2023-292 | |
| Date of Issue | 2024-03-06 (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 | RCS2023-292 |
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| Conference Information | |
| Committee | RCS SR SRW |
| Conference Date | 2024-03-13 - 2024-03-15 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | The University of Tokyo (Hongo Campus), and online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Communication Workshop |
| Paper Information | |
| Registration To | RCS |
| Conference Code | 2024-03-RCS-SR-SRW |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Study on Small Cell ON/OFF Control Using Different Frequency Cell Information |
| Sub Title (in English) | |
| Keyword(1) | HetNet |
| Keyword(2) | ON/OFF control |
| Keyword(3) | Deep Reinforcement Learning |
| Keyword(4) | PPO |
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| 1st Author's Name | Takaharu Kobayashi |
| 1st Author's Affiliation | Fujitsu Limited (Fujitsu) |
| 2nd Author's Name | Takashi Dateki |
| 2nd Author's Affiliation | Fujitsu Limited (Fujitsu) |
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| Speaker | Author-1 |
| Date Time | 2024-03-15 16:15:00 |
| Presentation Time | 25 minutes |
| Registration for | RCS |
| Paper # | RCS2023-292 |
| Volume (vol) | vol.123 |
| Number (no) | no.434 |
| Page | pp.176-181 |
| #Pages | 6 |
| Date of Issue | 2024-03-06 (RCS) |
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