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Paper Abstract and Keywords
Presentation 2022-01-25 15:45
Machine Learning-Based Adaptive Modulation and Coding with Generalized Mutual Information for Coded MIMO-OFDM Systems
Haruhiko Hasegawa, Yuto Hama, Hideki Ochiai (Yokohama Natl Univ) SR2021-83
Abstract (in Japanese) (See Japanese page) 
(in English) Adaptive modulation and coding (AMC) is a promising approach for enhancing the spectral efficiency and reliability by selective a suitable candidate from several predefined modulation and coding schemes (MCS). However, the conventional AMC approach based on the average signal-to-noise power ratio (SNR) may not identify the best MCS for a given realization of practical frequency-selective MIMO fading channels. To this end, we propose a machine learning (ML)-based AMC approach using the generalized mutual information (GMI), which is estimated by neural network (NN) and support vector regression (SVR) with robust feature extraction. Through computer simulations, we evaluate the effectiveness of our proposed system in terms of throughput and frame error rate (FER) performances.
Keyword (in Japanese) (See Japanese page) 
(in English) AMC / BICM / Generalized Mutual Information / Machine Learning / MIMO / OFDM / Turbo code /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 345, SR2021-83, pp. 118-124, Jan. 2022.
Paper # SR2021-83 
Date of Issue 2022-01-17 (SR) 
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 SR2021-83

Conference Information
Committee SR  
Conference Date 2022-01-24 - 2022-01-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SR 
Conference Code 2022-01-SR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Machine Learning-Based Adaptive Modulation and Coding with Generalized Mutual Information for Coded MIMO-OFDM Systems 
Sub Title (in English)  
Keyword(1) AMC  
Keyword(2) BICM  
Keyword(3) Generalized Mutual Information  
Keyword(4) Machine Learning  
Keyword(5) MIMO  
Keyword(6) OFDM  
Keyword(7) Turbo code  
Keyword(8)  
1st Author's Name Haruhiko Hasegawa  
1st Author's Affiliation Yokohama National University (Yokohama Natl Univ)
2nd Author's Name Yuto Hama  
2nd Author's Affiliation Yokohama National University (Yokohama Natl Univ)
3rd Author's Name Hideki Ochiai  
3rd Author's Affiliation Yokohama National University (Yokohama Natl Univ)
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Speaker Author-1 
Date Time 2022-01-25 15:45:00 
Presentation Time 25 minutes 
Registration for SR 
Paper # SR2021-83 
Volume (vol) vol.121 
Number (no) no.345 
Page pp.118-124 
#Pages 7 
Date of Issue 2022-01-17 (SR) 

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