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| Presentation | 2018-05-24 10:30 [Invited Talk] Wireless Link Quality Prediction And Wireless Control Through Machine Learning Takayuki Nishio (Kyoto Univ.)  SR2018-1 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this talk, wireless link quality prediction and control methods based on supervised learning from sensing information are introduced. In millimeter-wave (mmWave) communication, throughput estimation using camera imagery has been studied. Human blockage in mmWave communication sharply degrades link quality, and the blockage can be predicted from imagery since camera imagery contains geometry of transmitter, receiver, and pedestrian, and shape and mobility of pedestrian, which characterize human blockage in mmWave communications. Experimental results demonstrate that the scheme predicts throughput from imagery. In a spectrum sharing system, we have proposed a scheme to estimate region where harmful interference could occur and update primary exclusive region (PER) in order not to cause harmful interference. Support vector machine (SVM) learns interference region and decides appropriate boundary for PER. The simulation results demonstrate that the area of PER with the proposed scheme is smaller than that of the fixed circular PER setting with the same interference probability. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Machine Learning / Supervised Learning / Wireless Networks / Link Quality Prediction / mmWave / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 57, SR2018-1, pp. 1-6, May 2018. | |
| Paper # | SR2018-1 | |
| Date of Issue | 2018-05-17 (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 | SR2018-1 |
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| Conference Information | |
| Committee | SR |
| Conference Date | 2018-05-24 - 2018-05-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokyo big sight |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Technical Exhibition, Machine Learning, AI |
| Paper Information | |
| Registration To | SR |
| Conference Code | 2018-05-SR |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Wireless Link Quality Prediction And Wireless Control Through Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | Machine Learning |
| Keyword(2) | Supervised Learning |
| Keyword(3) | Wireless Networks |
| Keyword(4) | Link Quality Prediction |
| Keyword(5) | mmWave |
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| 1st Author's Name | Takayuki Nishio |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ.) |
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| Speaker | Author-1 |
| Date Time | 2018-05-24 10:30:00 |
| Presentation Time | 50 minutes |
| Registration for | SR |
| Paper # | SR2018-1 |
| Volume (vol) | vol.118 |
| Number (no) | no.57 |
| Page | pp.1-6 |
| #Pages | 6 |
| Date of Issue | 2018-05-17 (SR) |
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