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| Presentation | 2018-05-25 09:20 Traffic Control with Deep Reinforcement Learning Using an RGB-D Camera for Millimeter-wave Communications Tomoya Mikuma, Takayuki Nishio, Masahiro Morikura (Kyoto Univ.), Yusuke Asai, Ryo Miyatake (NTT)  MoNA2018-1 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In millimeter-wave (mmWave) communications, throughput is decreased seriously when line-of-sight paths are blocked by human bodies. In order to solve the throughput degradation problem, a proactive traffic control system based on RGB-D camera images has been proposed. The system predicts the human blockages and controls data transmission to each STA in order to increase the system throughput. The previous works employ the heuristic traffic control strategy which requires manual tuning suitable for a specific wireless communication environment. In order to solve the problem, this paper proposes a traffic control system with deep reinforcement learning using depth images obtained from an RGB-D camera and states of traffic buffers in a proxy server. The proposed system explores the optimal traffic control strategy appropriate to a wireless communication environment autonomously through trial and error, and it is expected to obtain a traffic control strategy improving the system throughput. The performance of the proposed traffic control system is evaluated by experiments. The experimental results show that the proposed system increases the system throughput as the learning progresses. In addition, the proposed system achieves higher performance compared with a simple heuristic algorithm. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | mmWave communication / IEEE 802.11ad / human blockage / RGB-D camera / deep reinforcement learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 56, MoNA2018-1, pp. 159-164, May 2018. | |
| Paper # | MoNA2018-1 | |
| Date of Issue | 2018-05-18 (MoNA) | |
| 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 | MoNA2018-1 |
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| Conference Information | |
| Committee | MoNA IPSJ-DPS IPSJ-MBL IPSJ-ITS |
| Conference Date | 2018-05-24 - 2018-05-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Eef Information Plaza |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | 5G, Mobile Applications, Ubiquitous Services, Mobile Distributed Cloud, ITS, etc. |
| Paper Information | |
| Registration To | MoNA |
| Conference Code | 2018-05-MoNA-DPS-MBL-ITS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Traffic Control with Deep Reinforcement Learning Using an RGB-D Camera for Millimeter-wave Communications |
| Sub Title (in English) | |
| Keyword(1) | mmWave communication |
| Keyword(2) | IEEE 802.11ad |
| Keyword(3) | human blockage |
| Keyword(4) | RGB-D camera |
| Keyword(5) | deep reinforcement learning |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Tomoya Mikuma |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 2nd Author's Name | Takayuki Nishio |
| 2nd Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 3rd Author's Name | Masahiro Morikura |
| 3rd Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 4th Author's Name | Yusuke Asai |
| 4th Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 5th Author's Name | Ryo Miyatake |
| 5th Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
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| Speaker | Author-1 |
| Date Time | 2018-05-25 09:20:00 |
| Presentation Time | 20 minutes |
| Registration for | MoNA |
| Paper # | MoNA2018-1 |
| Volume (vol) | vol.118 |
| Number (no) | no.56 |
| Page | pp.159-164 |
| #Pages | 6 |
| Date of Issue | 2018-05-18 (MoNA) |
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