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Paper Abstract and Keywords
Presentation 2020-08-21 10:30
[Encouragement Talk] Doppler frequency estimation of Superimposed Control Signal of multiple satellites by Deep Learning in LEO-MIMO
Ryo Okema (Nagoya Univ.), Daisuke Goto (NTT), Takaya Yamazato (Nagoya Univ.), Fumihiro Yamashita, Kiyohiko Itokawa (NTT) SAT2020-19
Abstract (in Japanese) (See Japanese page) 
(in English) This paper focuses on satellite MIMO (Multi-Input Multi-Output) technology to increase the capacity of Low Earth Orbit (LEO) satellite communications.
In previous research, LEO-MIMO communication requires control signals to estimate the Doppler frequencies of each satellite.
The control signal is allocated a different frequency band to avoid inter-carrier interference with other signals.
However, as the number of communication LEO satellites increases, the bandwidth of the control signal becomes wider and the bandwidth for the MIMO signal becomes narrower.
In other words, the problem is that the capacity of LEO-MIMO decreases with the increase in the number of communication LEO satellites.
Therefore, this study attempts to suppress the communication capacity reduction by superimposing control signals.
This technique can improve the bandwidth of the control signal is constant regardless of the number of satellites, and suppress capacity reduction regardless the number of satellites.
On the other hands, superimposed control signals technique degrades the Doppler frequency estimation accuracy due to inter-carrier interference.
To tackle of the problem, we propose the novel Doppler frequency estimation using Deep learning techniques.
This paper deal with Doppler shift estimation for control signals with three or more superimposed waveforms and unlearned waveforms.
In order to improve the estimation accuracy, we employed convolutional neural networks in addition to deep neural networks and compared their performance.
Keyword (in Japanese) (See Japanese page) 
(in English) Low earth orbit satellite / MIMO satellite communications / Deep learning / Signal detection / Doppler shift estimation / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 129, SAT2020-19, pp. 47-52, Aug. 2020.
Paper # SAT2020-19 
Date of Issue 2020-08-13 (SAT) 
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 SAT2020-19

Conference Information
Committee SAT RCS  
Conference Date 2020-08-20 - 2020-08-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SAT 
Conference Code 2020-08-SAT-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Doppler frequency estimation of Superimposed Control Signal of multiple satellites by Deep Learning in LEO-MIMO 
Sub Title (in English)  
Keyword(1) Low earth orbit satellite  
Keyword(2) MIMO satellite communications  
Keyword(3) Deep learning  
Keyword(4) Signal detection  
Keyword(5) Doppler shift estimation  
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1st Author's Name Ryo Okema  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Daisuke Goto  
2nd Author's Affiliation NTT Access Network Service Systems Laboratories (NTT)
3rd Author's Name Takaya Yamazato  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Fumihiro Yamashita  
4th Author's Affiliation NTT Access Network Service Systems Laboratories (NTT)
5th Author's Name Kiyohiko Itokawa  
5th Author's Affiliation NTT Access Network Service Systems Laboratories (NTT)
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Speaker Author-1 
Date Time 2020-08-21 10:30:00 
Presentation Time 25 minutes 
Registration for SAT 
Paper # SAT2020-19 
Volume (vol) vol.120 
Number (no) no.129 
Page pp.47-52 
#Pages
Date of Issue 2020-08-13 (SAT) 


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