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Paper Abstract and Keywords
Presentation 2024-01-18 09:55
A Study on Autoencoder-aided Data-Driven Tuning for Linear Dispersion Code
Arata Kameda, Shinsuke Ibi (Doshisha Univ.), Takumi Takahashi (Osaka Univ.), Hisato Iwai (Doshisha Univ.) IT2023-31 SIP2023-64 RCS2023-206
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we consider the application of wireless autoencoder (WAE) to a model of code generation rules for linear dispersion codes (LDC). LDC is a coding scheme in which the modulation symbols are distributed by a dispersion matrix as much as possible in both the spatial and time domains to achieve high reliability owing to the spatio-temporal diversity effect and high transmission rates owing to the spatial multiplexing effect without compromising signal detection accuracy. Typically, the dispersion matrix is numerically searched using random numbers to obtain a higher discrete-input continuous-output memoryless channel (DCMC) capacity. This method requires a significant amount of time to search for a large dispersion matrix. To solve this problem, this paper proposes to improve search efficiency by configuring WAE, a type of machine learning, as a neural network for generating dispersion matrices. In addition, WAE is introduced for signal constellation generation of modulation symbols as well as dispersion matrix generation to improve signal detection accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) Linear dispersion code / signal constellation / wireless autoencoder / data-driven tuning / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 340, RCS2023-206, pp. 7-12, Jan. 2024.
Paper # RCS2023-206 
Date of Issue 2024-01-11 (IT, SIP, 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 IT2023-31 SIP2023-64 RCS2023-206

Conference Information
Committee SIP IT RCS  
Conference Date 2024-01-18 - 2024-01-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To RCS 
Conference Code 2024-01-SIP-IT-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Autoencoder-aided Data-Driven Tuning for Linear Dispersion Code 
Sub Title (in English)  
Keyword(1) Linear dispersion code  
Keyword(2) signal constellation  
Keyword(3) wireless autoencoder  
Keyword(4) data-driven tuning  
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1st Author's Name Arata Kameda  
1st Author's Affiliation Doshisha University (Doshisha Univ.)
2nd Author's Name Shinsuke Ibi  
2nd Author's Affiliation Doshisha University (Doshisha Univ.)
3rd Author's Name Takumi Takahashi  
3rd Author's Affiliation Osaka University (Osaka Univ.)
4th Author's Name Hisato Iwai  
4th Author's Affiliation Doshisha University (Doshisha Univ.)
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Speaker Author-1 
Date Time 2024-01-18 09:55:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # IT2023-31, SIP2023-64, RCS2023-206 
Volume (vol) vol.123 
Number (no) no.338(IT), no.339(SIP), no.340(RCS) 
Page pp.7-12 
#Pages 6 
Date of Issue 2024-01-11 (IT, SIP, RCS) 

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