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Paper Abstract and Keywords
Presentation 2018-05-24 15:05
A Study of Proactive Beam Forming Control using Machine Learning for 5G Mobile Communication System
Takashi Seyama, Teppei Oyama, Takashi Dateki (Fujitsu Lab.) SR2018-7
Abstract (in Japanese) (See Japanese page) 
(in English) In fifth generation mobile communication systems, beam forming have been studied in order to compensate increase of pathloss at higher frequency than 4G. In beam forming at high frequency, the received power will degrade when UE moves behind buildings or traffic signs or a human bodies. In this paper, we proposed a proactive beam forming control on the basis of prediction of received power change using machine learning techniques to mitigate blockage effect by static objects when UE moves. As a preliminary study, we study prediction of the received power degradation event by means of neural network whose inputs are time series data of beam index and received power fed back by UE. We train the prediction model using training data generated by computer simulations and evaluate the success rate, the miss detection rate and the false alarm rate.
Keyword (in Japanese) (See Japanese page) 
(in English) 5G / Beam forming / Proactive beam forming control / Machine Learning / Neural Network / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 57, SR2018-7, pp. 43-48, May 2018.
Paper # SR2018-7 
Date of Issue 2018-05-17 (SR) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 SR2018-7

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) A Study of Proactive Beam Forming Control using Machine Learning for 5G Mobile Communication System 
Sub Title (in English)  
Keyword(1) 5G  
Keyword(2) Beam forming  
Keyword(3) Proactive beam forming control  
Keyword(4) Machine Learning  
Keyword(5) Neural Network  
1st Author's Name Takashi Seyama  
1st Author's Affiliation FUJITSU LABORATORIES LTD. (Fujitsu Lab.)
2nd Author's Name Teppei Oyama  
2nd Author's Affiliation FUJITSU LABORATORIES LTD. (Fujitsu Lab.)
3rd Author's Name Takashi Dateki  
3rd Author's Affiliation FUJITSU LABORATORIES LTD. (Fujitsu Lab.)
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Date Time 2018-05-24 15:05:00 
Presentation Time 25 
Registration for SR 
Paper # IEICE-SR2018-7 
Volume (vol) IEICE-118 
Number (no) no.57 
Page pp.43-48 
#Pages IEICE-6 
Date of Issue IEICE-SR-2018-05-17 

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