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Paper Abstract and Keywords
Presentation 2020-07-09 15:00
[Invited Lecture] Blind Adaptive Array Interference Suppression Performance with Deep Learning based SIR Estimation
Kazuki Maruta (Tokyo Tech), Shun Kojima (Chiba Univ.), Daisuke Hisano (Osaka Univ.), Yu Nakayama (TUAT) RCC2020-8 NS2020-37 RCS2020-71 SR2020-16 SeMI2020-8
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a blind interference estimation via deep learning approach exploiting the visualized wireless signal information, that is, IQ constellation. Co-channel interference becomes more extensive due to frequency resource exhaustion and small cell deployment which had been triggered by mobile traffic explosion. Multi-antenna signal processing known to blind adaptive array (BAA) is an effective means to suppress co-channel interference without any a priori information such as channel state information. Unfortunately, blind algorithms have their applicable regions depending on the signal-to-interference (SIR) at array input. These algorithms should be optimally selected according to interference level. Here we investigates the possibility of the SIR classification by the multi-layered deep convolutional neural network (CNN). Constellation images where includes the desired and interference signals are used for model training. Further, we clarify the interference suppression performance of BAAs using estimated SIR values.
Keyword (in Japanese) (See Japanese page) 
(in English) Adaptive array / Interference suppression / Constant modulus algorithm / Power inversion / Interference estimation / Deep learning / Constellation /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 89, RCS2020-71, pp. 79-83, July 2020.
Paper # RCS2020-71 
Date of Issue 2020-07-01 (RCC, NS, RCS, SR, SeMI) 
ISSN 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 RCC2020-8 NS2020-37 RCS2020-71 SR2020-16 SeMI2020-8

Conference Information
Committee SR NS SeMI RCC RCS  
Conference Date 2020-07-08 - 2020-07-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication and Network Technology of the AI Age, M2M (Machine-to-Machine),D2D (Device-to-Device),IoT(Internet of Things), etc 
Paper Information
Registration To RCS 
Conference Code 2020-07-SR-NS-SeMI-RCC-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Blind Adaptive Array Interference Suppression Performance with Deep Learning based SIR Estimation 
Sub Title (in English)  
Keyword(1) Adaptive array  
Keyword(2) Interference suppression  
Keyword(3) Constant modulus algorithm  
Keyword(4) Power inversion  
Keyword(5) Interference estimation  
Keyword(6) Deep learning  
Keyword(7) Constellation  
Keyword(8)  
1st Author's Name Kazuki Maruta  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
2nd Author's Name Shun Kojima  
2nd Author's Affiliation Chiba University (Chiba Univ.)
3rd Author's Name Daisuke Hisano  
3rd Author's Affiliation Osaka University (Osaka Univ.)
4th Author's Name Yu Nakayama  
4th Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
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Speaker Author-1 
Date Time 2020-07-09 15:00:00 
Presentation Time 30 minutes 
Registration for RCS 
Paper # RCC2020-8, NS2020-37, RCS2020-71, SR2020-16, SeMI2020-8 
Volume (vol) vol.120 
Number (no) no.87(RCC), no.88(NS), no.89(RCS), no.90(SR), no.91(SeMI) 
Page pp.37-41(RCC), pp.37-41(NS), pp.79-83(RCS), pp.43-47(SR), pp.31-35(SeMI) 
#Pages
Date of Issue 2020-07-01 (RCC, NS, RCS, SR, SeMI) 


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