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Paper Abstract and Keywords
Presentation 2026-03-06 15:00
Adaptive MIMO Precoding Control Using Deep Unfolding for Wireless Communications
Kaita Tsuru, Kazuhiko Fukawa (Science Tokyo) RCS2025-296
Abstract (in Japanese) (See Japanese page) 
(in English) In downlink systems of multiple-input multiple-output (MIMO) wireless communications, linear precoding should be employed to suppress inter-user interference, but conventional precoding schemes such as minimum mean square error (MMSE) are highly susceptible to estimation errors of channel state information (CSI) and changes in CSI statistical properties because they fix the regularization parameter. This report proposes a precoding scheme robust against CSI estimation errors using Deep Unfolding, which unfolds the MMSE computation process into neural network layers. The proposed scheme iteratively estimates two parameters at each layer, the regularization scaling coefficient and the linear interpolation weight, to dynamically control the trade-off between desired signal power maximization and interference suppression. These parameters are learned via unsupervised learning under the criterion of signal-to-interference-plus-noise ratio (SINR) maximization. Computer simulations considering channel estimation errors demonstrate that under the standard condition that the total number of transmit antennas far exceeds the number of user terminals, the proposed scheme achieves spectral efficiency comparable to that of zero forcing (ZF) and MMSE. Conversely, under the overload condition that the number of user terminals exceeds the total number of transmit antennas, the proposed scheme outperforms conventional ones. The trained model also operates effectively even when the number of user terminals and coordination schemes differ from those during the training. It is also shown that the proposed scheme can drastically reduce the computational complexity of the conventional ones that grows rapidly with the number of user terminals.
Keyword (in Japanese) (See Japanese page) 
(in English) MIMO / Precoding / MMSE / ZF / Deep Unfolding / Channel estimation error / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 387, RCS2025-296, pp. 215-220, March 2026.
Paper # RCS2025-296 
Date of Issue 2026-02-25 (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 RCS2025-296

Conference Information
Committee RCS SR SRW  
Conference Date 2026-03-04 - 2026-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo University of Science 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Communication Workshop 
Paper Information
Registration To RCS 
Conference Code 2026-03-RCS-SR-SRW 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Adaptive MIMO Precoding Control Using Deep Unfolding for Wireless Communications 
Sub Title (in English)  
Keyword(1) MIMO  
Keyword(2) Precoding  
Keyword(3) MMSE  
Keyword(4) ZF  
Keyword(5) Deep Unfolding  
Keyword(6) Channel estimation error  
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Keyword(8)  
1st Author's Name Kaita Tsuru  
1st Author's Affiliation Institute of Science Tokyo (Science Tokyo)
2nd Author's Name Kazuhiko Fukawa  
2nd Author's Affiliation Institute of Science Tokyo (Science Tokyo)
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Speaker Author-1 
Date Time 2026-03-06 15:00:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # RCS2025-296 
Volume (vol) vol.125 
Number (no) no.387 
Page pp.215-220 
#Pages 6 
Date of Issue 2026-02-25 (RCS) 

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