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Paper Abstract and Keywords
Presentation 2020-06-25 14:55
A Study on the Behavior of Each LLR in Gaussian Belief Propagation
Daniel Akira Ando, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, Junichiro Hagiwara, Takanori Sato (Hokkaido Univ.) RCS2020-39
Abstract (in Japanese) (See Japanese page) 
(in English) We have entered the era of the Internet of Things (IoT), where everything can now be connected to the internet. In order to expand even more the use of IoT devices and services, massive MIMO, which achieves massive multiple access, will attract much more attention. However, simultaneous transmission from a large number of IoT devices increases the complexity of signal detection significantly. As a means of solving this issue, the Gaussian belief propagation algorithm has been proposed. The Gaussian belief propagation described on a bipartite factor graph is an algorithm to detect individual transmitted signals based on message passing. In this study, we investigated the behavior of messages in the factor graph. As a result, we have found that error-free detection is achieved even though nearly 40% of the polarity of messages are incorrect. This property may be applied to decrease the complexity of Gaussian belief propagation in the future.
Keyword (in Japanese) (See Japanese page) 
(in English) Massive MIMO / Signal Detection / Gaussian Belief Propagation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 74, RCS2020-39, pp. 97-102, June 2020.
Paper # RCS2020-39 
Date of Issue 2020-06-17 (RCS) 
ISSN Print edition: ISSN 0913-5685  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)
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Conference Information
Committee RCS  
Conference Date 2020-06-24 - 2020-06-26 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) First Presentation in IEICE Technical Committee, Resource Control, Scheduling, Wireless Communications, etc. 
Paper Information
Registration To RCS 
Conference Code 2020-06-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on the Behavior of Each LLR in Gaussian Belief Propagation 
Sub Title (in English)  
Keyword(1) Massive MIMO  
Keyword(2) Signal Detection  
Keyword(3) Gaussian Belief Propagation  
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1st Author's Name Daniel Akira Ando  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Toshihiko Nishimura  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Takeo Ohgane  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Yasutaka Ogawa  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
5th Author's Name Junichiro Hagiwara  
5th Author's Affiliation Hokkaido University (Hokkaido Univ.)
6th Author's Name Takanori Sato  
6th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker
Date Time 2020-06-25 14:55:00 
Presentation Time 25 
Registration for RCS 
Paper # IEICE-RCS2020-39 
Volume (vol) IEICE-120 
Number (no) no.74 
Page pp.97-102 
#Pages IEICE-6 
Date of Issue IEICE-RCS-2020-06-17 


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