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| Presentation | 2020-03-05 11:15 An Application of Deep Learning to CoMP Transmission Employing Vehicle Position Information in Taxi Radio Systems Kazuki Kojima, Yukiko Shimbo, Hirofumi Suganuma, Fumiaki Maehara (Waseda Univ.)  RCS2019-355 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This report proposes a coordinated multi-point (CoMP) transmission method based on deep learning for taxi radio systems to prevent inter-cell interference (ICI). In CoMP, it is essential to select whether to use simultaneous transmission or time division multiplexing (TDM) considering the effect of the ICI. The feature of the proposed method is to determine such a transmission mode by using vehicle position information as taxi radio systems have such position information. Moreover, the proposed method makes it possible to avoid the online system capacity calculation also required for CoMP thanks to the use of deep learning. The effectiveness of the proposed method is demonstrated in comparison with a traditional online calculation method under the practical scenario based on the taxi radio system in Japan. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | taxi radio systems / multi-cell / coordinated multi-point (CoMP) / vehicle position information / deep learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 448, RCS2019-355, pp. 189-193, March 2020. | |
| Paper # | RCS2019-355 | |
| Date of Issue | 2020-02-26 (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 | RCS2019-355 |
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| Conference Information | |
| Committee | RCS SR SRW |
| Conference Date | 2020-03-04 - 2020-03-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokyo Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Communication Workshop |
| Paper Information | |
| Registration To | RCS |
| Conference Code | 2020-03-RCS-SR-SRW |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Application of Deep Learning to CoMP Transmission Employing Vehicle Position Information in Taxi Radio Systems |
| Sub Title (in English) | |
| Keyword(1) | taxi radio systems |
| Keyword(2) | multi-cell |
| Keyword(3) | coordinated multi-point (CoMP) |
| Keyword(4) | vehicle position information |
| Keyword(5) | deep learning |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Kazuki Kojima |
| 1st Author's Affiliation | Waseda University (Waseda Univ.) |
| 2nd Author's Name | Yukiko Shimbo |
| 2nd Author's Affiliation | Waseda University (Waseda Univ.) |
| 3rd Author's Name | Hirofumi Suganuma |
| 3rd Author's Affiliation | Waseda University (Waseda Univ.) |
| 4th Author's Name | Fumiaki Maehara |
| 4th Author's Affiliation | Waseda University (Waseda Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-03-05 11:15:00 |
| Presentation Time | 20 minutes |
| Registration for | RCS |
| Paper # | RCS2019-355 |
| Volume (vol) | vol.119 |
| Number (no) | no.448 |
| Page | pp.189-193 |
| #Pages | 5 |
| Date of Issue | 2020-02-26 (RCS) |
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