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Paper Abstract and Keywords
Presentation 2016-06-23 09:50
Channel Compression for Massive MIMO based on Principal Component Analysis with Channel Prediction and Differential Quantization
Rei Nagashima, Tomoaki Ohtsuki (Keio Univ.), Wenjie Jiang, Yasushi Takatori, Tadao Nakagawa (NTT) RCS2016-59
Abstract (in Japanese) (See Japanese page) 
(in English) Massive MIMO (multiple-input multiple-output) is one of the key technologies to realize 5G (5th Generation).However, there exists an issue such as the increase of the amount of feedback of channel state information (CSI) from the receiver to the transmitter, due to the enormous number of antennas.For the purpose of solving this issue, there exists the technique to compress CSI to a lower dimension matrix and decrease the amount of feedback, by using principal component analysis (PCA).In this method, the compression matrix used in PCA is generated based on the past CSI at the receiver, which leads to the degradation of transmission rate due to the channel variation during the feedback.Moreover, in this method, the amount of feedback is dependent on the size of the compression matrix, and if the size of the compression matrix is large, the effect of the reduction of the feedback becomes small.In this report, to solve these problems, we propose the method based on PCA with channel prediction and differential quantization oh the channels and the compression matrices.By the computer simulation, it is shown that the system capacity is increased by generating the compression matrix from the predicted channel, and the amount of feedback is reduced by quantizing the difference of the channels and the compression matrices.
Keyword (in Japanese) (See Japanese page) 
(in English) Massive MIMO / Channel Compression / Channel Prediction / Principal Component Analysis / 5G / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 110, RCS2016-59, pp. 75-80, June 2016.
Paper # RCS2016-59 
Date of Issue 2016-06-15 (RCS) 
ISSN Print edition: ISSN 0913-5685    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 RCS2016-59

Conference Information
Committee RCS  
Conference Date 2016-06-22 - 2016-06-24 
Place (in Japanese) (See Japanese page) 
Place (in English) Univ. of the Ryukyus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) First Presentation in IEICE Technical Committee, Railroad Communications, Inter-Vehicle Communications, Road to Vehicle Communications, Resource Control, Scheduling, Wireless Communication Systems, etc. 
Paper Information
Registration To RCS 
Conference Code 2016-06-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Channel Compression for Massive MIMO based on Principal Component Analysis with Channel Prediction and Differential Quantization 
Sub Title (in English)  
Keyword(1) Massive MIMO  
Keyword(2) Channel Compression  
Keyword(3) Channel Prediction  
Keyword(4) Principal Component Analysis  
Keyword(5) 5G  
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1st Author's Name Rei Nagashima  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Tomoaki Ohtsuki  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Wenjie Jiang  
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
4th Author's Name Yasushi Takatori  
4th Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
5th Author's Name Tadao Nakagawa  
5th Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
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Speaker Author-1 
Date Time 2016-06-23 09:50:00 
Presentation Time 10 minutes 
Registration for RCS 
Paper # RCS2016-59 
Volume (vol) vol.116 
Number (no) no.110 
Page pp.75-80 
#Pages 6 
Date of Issue 2016-06-15 (RCS) 

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