Paper Abstract and Keywords |
Presentation |
2013-10-18 14:00
Q-Learning Based Cell Selection in Heterogeneous Networks Toshihito Kudo, Tomoaki Ohtsuki (Keio Univ.) RCS2013-167 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Cell range expansion (CRE) expands a pico cell range virtually by adding a bias value to the pico received power, instead of increasing transmit power of the pico base station (PBS). Although it can make coverage, cell-edge throughput, and overall network throughput improved, cell selection becomes complicated. UE outages can be reduced with bias values set by each UE. However, because of the difficulty of setting bias value of each UE, many studies about CRE have used a common bias value among all user equipments (UEs). In this report, we propose a scheme to select a cell by using Q-learning algorithm where each UE learns which cell to select to reduce the number of UE outages from its past experience independently. Simulation results show that, compared to the practical common bias value setting, the proposed scheme reduces the number of UE outages and improves network throughput in most cases. Moreover, instead of a small increase of UE outages, it also reduces the required memory size compared with our previous proposed method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Heterogeneous network / Cell range expansion / Cell selection / Picocell / Reinforcement learning / Q-learning / Multi-agent system / |
Reference Info. |
IEICE Tech. Rep., vol. 113, no. 246, RCS2013-167, pp. 145-150, Oct. 2013. |
Paper # |
RCS2013-167 |
Date of Issue |
2013-10-10 (RCS) |
ISSN |
Print edition: ISSN 0913-5685 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) |
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RCS2013-167 |
Conference Information |
Committee |
RCS |
Conference Date |
2013-10-17 - 2013-10-18 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Sophia Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Wireless Communication Schemes, Wireless Communication Systems, Wireless Standards, etc. |
Paper Information |
Registration To |
RCS |
Conference Code |
2013-10-RCS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Q-Learning Based Cell Selection in Heterogeneous Networks |
Sub Title (in English) |
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Keyword(1) |
Heterogeneous network |
Keyword(2) |
Cell range expansion |
Keyword(3) |
Cell selection |
Keyword(4) |
Picocell |
Keyword(5) |
Reinforcement learning |
Keyword(6) |
Q-learning |
Keyword(7) |
Multi-agent system |
Keyword(8) |
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1st Author's Name |
Toshihito Kudo |
1st Author's Affiliation |
Keio University (Keio Univ.) |
2nd Author's Name |
Tomoaki Ohtsuki |
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Keio University (Keio Univ.) |
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Speaker |
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Date Time |
2013-10-18 14:00:00 |
Presentation Time |
20 minutes |
Registration for |
RCS |
Paper # |
RCS2013-167 |
Volume (vol) |
vol.113 |
Number (no) |
no.246 |
Page |
pp.145-150 |
#Pages |
6 |
Date of Issue |
2013-10-10 (RCS) |
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