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Paper Abstract and Keywords
Presentation 2024-08-30 13:00
A Study on Autoencoder-Aided Data-Driven Tuning for Differential Linear Dispersion Code
Arata Kameda, Shinsuke Ibi (Doshisha Univ.), Takumi Takahashi (Osaka Univ.), Hisato Iwai (Doshisha Univ.) RCS2024-130
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose the application of a wireless autoencoder (WAE) to a model of code generation rules of a differential linear dispersion code (DLDC) in blind multi-input multi-output (MIMO) communications using probabilistic data association (PDA) as a signal demodulation method.DLDC is a coding scheme that simultaneously maximizes space-time diversity and spatial multiplexing effects by dispersing modulation symbols in both the spatial and temporal domains while realizing blind signal separation (BSS).Typically, dispersion codes are searched numerically to achieve a lower pairwise error rate (PER) using random numbers.The objective of this study is to increase the code dimension of DLDC. However, searching for the optimal variance matrix becomes difficult when the dimension of the distributed code increases.On the other hand, as the size of the dispersion code becomes larger, the amount of computation for maximum likelihood estimation detection (MLD) at the receiver side becomes problematic.As a solution, PDA is utilized as a signal detector to reduce the computational burden, and WAE, a type of machine learning, is configured as a neural network for generating the dispersion matrix to improve the efficiency of the search.
Keyword (in Japanese) (See Japanese page) 
(in English) Differential linear dispersion code / probabilistic data association / wireless autoencoder / data-driven tuning / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 166, RCS2024-130, pp. 78-83, Aug. 2024.
Paper # RCS2024-130 
Date of Issue 2024-08-22 (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 RCS2024-130

Conference Information
Committee SAT RCS  
Conference Date 2024-08-29 - 2024-08-30 
Place (in Japanese) (See Japanese page) 
Place (in English) CUL-PORT(Kochi City) (Temporary) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Satellite Communications, Broadcasting, Forward Error Correction, Wireless Communications, etc. 
Paper Information
Registration To RCS 
Conference Code 2024-08-SAT-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 Differential Linear Dispersion Code 
Sub Title (in English)  
Keyword(1) Differential linear dispersion code  
Keyword(2) probabilistic data association  
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 2024-08-30 13:00:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # RCS2024-130 
Volume (vol) vol.124 
Number (no) no.166 
Page pp.78-83 
#Pages 6 
Date of Issue 2024-08-22 (RCS) 

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