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Paper Abstract and Keywords
Presentation 2022-03-04 16:25
Behavioral Modeling of RF Power Amplifiers using Binary Neural Network
Taishi Watanabe, Takeo Ohseki, Kosuke Yamazaki (KDDI Research) RCS2021-293
Abstract (in Japanese) (See Japanese page) 
(in English) With the increase in bandwidth in mobile communication systems, the effect of performance degradation due to nonlinear distortion generated in power amplifiers becomes larger. If this is dealt with by improving the characteristics of the amplifiers, the power efficiency of the transmitter will be greatly reduced. Therefore, in addition to improving the characteristics of the amplifiers, nonlinear compensation is necessary. In order to perform nonlinear distortion compensation, it is necessary to accurately model the operation of power amplifiers. In recent years, the use of neural networks has been proposed to model the complex distortions that occur in a wide bandwidth. However, the nonlinear compensation using neural networks is computationally expensive. On the other hand, in the field of neural networks, binary neural networks, in which the neural network is represented by a single bit, have recently been attracting attention for embedded devices. In this paper, we apply binary neural networks to modeling the operation of power amplifiers, and evaluate their performance and computational complexity.
Keyword (in Japanese) (See Japanese page) 
(in English) Neural Network / Binary Neural Network / Non-linear Compensation / Digital Pre-distortion / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 391, RCS2021-293, pp. 207-211, March 2022.
Paper # RCS2021-293 
Date of Issue 2022-02-23 (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 RCS2021-293

Conference Information
Committee RCS SR SRW  
Conference Date 2022-03-02 - 2022-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Communication Workshop 
Paper Information
Registration To RCS 
Conference Code 2022-03-RCS-SR-SRW 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Behavioral Modeling of RF Power Amplifiers using Binary Neural Network 
Sub Title (in English)  
Keyword(1) Neural Network  
Keyword(2) Binary Neural Network  
Keyword(3) Non-linear Compensation  
Keyword(4) Digital Pre-distortion  
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Keyword(6)  
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1st Author's Name Taishi Watanabe  
1st Author's Affiliation KDDI Research, Inc. (KDDI Research)
2nd Author's Name Takeo Ohseki  
2nd Author's Affiliation KDDI Research, Inc. (KDDI Research)
3rd Author's Name Kosuke Yamazaki  
3rd Author's Affiliation KDDI Research, Inc. (KDDI Research)
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Speaker Author-1 
Date Time 2022-03-04 16:25:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # RCS2021-293 
Volume (vol) vol.121 
Number (no) no.391 
Page pp.207-211 
#Pages 5 
Date of Issue 2022-02-23 (RCS) 

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