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| Presentation | 2021-12-17 14:30 [Invited Lecture] Energy-Efficient DQN-based User Association for Sub6GHz/mmWave Networks Megumi Kaneko, Thi Ha Ly Dinh (NII), Keisuke Wakao, Kenichi Kawamura, Takatsune Moriyama, Yasushi Takatori (NTT)  NS2021-109 RCS2021-192 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This work investigates the design of an energy-efficient Deep Q-Network (DQN) implemented at the user device, whose purpose is to optimize its association to multiple access points (AP) in a Beyond 5G (B5G) Sub-6GHz and mmWave integrated network. To better cope with dynamic mobile environments, we first propose an adaptive epsilon-greedy policy at each user DQN in order to maximize the long-term sum-rate while simultaneously satisfying the Quality of Service (QoS) constraints of different applications. We then provide the detailed analysis of the energy consumed by each user device, in particular the power for DQN processing and for data movement. The trade-off between network performance in terms of sum-rate and QoS outage probability, and energy consumption at the user side is evaluated. Numerical results not only show the effectiveness of the proposed method compared to baseline, but also reveal the tremendous energy costs required by the default user DQN, underlining the importance of such energy-efficiency aware protocol design. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Deep Reinforcement Learning / energy efficiency / User-to-multiple access points association / Deep Q-Network / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 302, RCS2021-192, pp. 88-88, Dec. 2021. | |
| Paper # | RCS2021-192 | |
| Date of Issue | 2021-12-09 (NS, 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 | NS2021-109 RCS2021-192 |
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| Conference Information | |
| Committee | RCS NS |
| Conference Date | 2021-12-16 - 2021-12-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nara-ken Bunka Kaikan and Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Multi-hop/Relay/Cooperation, Disaster-resistant wireless network, Sensor/Mesh network, Ad-hoc network, D2D/M2M, Wireless network coding, Handover/AP switching/Connected cell control/Load balancing among base stations/Mobile network dynamic reconfiguration, QoS/QoE assurance, Wireless VoIP, IoT, Edge computing, etc. |
| Paper Information | |
| Registration To | RCS |
| Conference Code | 2021-12-RCS-NS |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Energy-Efficient DQN-based User Association for Sub6GHz/mmWave Networks |
| Sub Title (in English) | |
| Keyword(1) | Deep Reinforcement Learning |
| Keyword(2) | energy efficiency |
| Keyword(3) | User-to-multiple access points association |
| Keyword(4) | Deep Q-Network |
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| 1st Author's Name | Megumi Kaneko |
| 1st Author's Affiliation | National Institute of Informatics (NII) |
| 2nd Author's Name | Thi Ha Ly Dinh |
| 2nd Author's Affiliation | National Institute of Informatics (NII) |
| 3rd Author's Name | Keisuke Wakao |
| 3rd Author's Affiliation | NTT Corporation (NTT) |
| 4th Author's Name | Kenichi Kawamura |
| 4th Author's Affiliation | NTT Corporation (NTT) |
| 5th Author's Name | Takatsune Moriyama |
| 5th Author's Affiliation | NTT Corporation (NTT) |
| 6th Author's Name | Yasushi Takatori |
| 6th Author's Affiliation | NTT Corporation (NTT) |
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| Speaker | Author-1 |
| Date Time | 2021-12-17 14:30:00 |
| Presentation Time | 25 minutes |
| Registration for | RCS |
| Paper # | NS2021-109, RCS2021-192 |
| Volume (vol) | vol.121 |
| Number (no) | no.301(NS), no.302(RCS) |
| Page | p.65(NS), p.88(RCS) |
| #Pages | 1 |
| Date of Issue | 2021-12-09 (NS, RCS) |
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