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Paper Abstract and Keywords
Presentation 2012-01-27 14:20
Learning-based Cell Selection for Open-access Femtocell Networks
Chaima Dhahri, Tomoaki Ohtsuki (Keio Univ.) SIP2011-121 RCS2011-310
Abstract (in Japanese) (See Japanese page) 
(in English) In an open-access femtocell networks, nearby cellular users (Macro User: MU) may join, through a handover procedure, one of the neighboring femtocells in order to enhance their capacity. To avoid undesirable effects such as the ping-pong effect after a handover, the effectiveness of cell selection method must be ensured. Previous work related to such a problem is based on instantaneous measure of single or multiple metrics, e.g. capacity, received signal strength (RSS), load, etc. However, the measure at present time does not reflect the cell performance in the future. Hence the need of a new cell selection that predicts the horizon. In this paper, we propose a Reinforcement Learning (RL) Q-algorithm as a generic solution for the cell selection problem in a non-stationary femtocell network. The simulation results show the benefits of using learning in terms of MU gained capacity compared to a random and a least loaded (LL) algorithms and in terms of number of handovers compared to capacity-based cell selection method.
Keyword (in Japanese) (See Japanese page) 
(in English) femtocell network / cell selection / Reinforcement learning / handover decision / / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 404, RCS2011-310, pp. 245-250, Jan. 2012.
Paper # RCS2011-310 
Date of Issue 2012-01-19 (SIP, RCS) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 SIP2011-121 RCS2011-310

Conference Information
Committee RCS SIP  
Conference Date 2012-01-26 - 2012-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukuoka Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Signal Processing for Wireless Systems, etc. 
Paper Information
Registration To RCS 
Conference Code 2012-01-RCS-SIP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Learning-based Cell Selection for Open-access Femtocell Networks 
Sub Title (in English)  
Keyword(1) femtocell network  
Keyword(2) cell selection  
Keyword(3) Reinforcement learning  
Keyword(4) handover decision  
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1st Author's Name Chaima Dhahri  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Tomoaki Ohtsuki  
2nd Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2012-01-27 14:20:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # SIP2011-121, RCS2011-310 
Volume (vol) vol.111 
Number (no) no.403(SIP), no.404(RCS) 
Page pp.245-250 
#Pages 6 
Date of Issue 2012-01-19 (SIP, RCS) 

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