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Paper Abstract and Keywords
Presentation 2022-06-16 15:20
A study on LLR Synthesis Method for Beam-Domain Local LMMSE Detection in mmWave Large MIMO
Takumi Yoshida, Takumi Takahashi (Osaka Univ.), Shinsuke Ibi (Doshisha Univ.), Seiichi Sampei (Osaka Univ.) RCS2022-51
Abstract (in Japanese) (See Japanese page) 
(in English) As a low-complexity multi-user detector for uplink millimeter-wave (mmWave) large multi-user MIMO (Multi-Input Multi-Output), beam-domain local linear minimum mean square error (LLMMSE) filters, which consist of a linear filter for each user on a small number of receive digital beams, have been proposed. In the previous study, we proposed a method of selecting multiple LLMMSE filters for each user and combining log-likelihood ratios (LLRs) calculated from their output values to improve detection accuracy, and an extension to iterative detection. However, multiple LLMMSE filters selected to maximize the desired signal information overlap on the signal space in the beam domain, and the combined LLRs are strongly correlated to each other. Consequently, simple addition of LLRs cannot properly combine the information, resulting in performance degradation, especially when extended to the iterative detection scheme. To tackle this problem, this paper proposes a method of combining LLRs that takes into account the correlation between LLRs by calculating the LLRs corresponding to the overlapped portions of selected LLMMSE filters and subtracting them from the typical combined LLRs. In addition, by utilizing the Schur complement matrix, the amount of additional operations becomes negligibly small. Finally, we evaluate the bit error rate (BER) performance and the amount of detection operations via computer simulations to confirm the efficacy of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Millimeter-wave large MIMO detection / Digital beamforming / Local LMMSE filter / Iterative detection / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 73, RCS2022-51, pp. 162-167, June 2022.
Paper # RCS2022-51 
Date of Issue 2022-06-08 (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 RCS2022-51

Conference Information
Committee RCS  
Conference Date 2022-06-15 - 2022-06-17 
Place (in Japanese) (See Japanese page) 
Place (in English) University of the Ryukyus, Senbaru Campus and 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 2022-06-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study on LLR Synthesis Method for Beam-Domain Local LMMSE Detection in mmWave Large MIMO 
Sub Title (in English)  
Keyword(1) Millimeter-wave large MIMO detection  
Keyword(2) Digital beamforming  
Keyword(3) Local LMMSE filter  
Keyword(4) Iterative detection  
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1st Author's Name Takumi Yoshida  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Takumi Takahashi  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Shinsuke Ibi  
3rd Author's Affiliation Doshisha University (Doshisha Univ.)
4th Author's Name Seiichi Sampei  
4th Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2022-06-16 15:20:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # RCS2022-51 
Volume (vol) vol.122 
Number (no) no.73 
Page pp.162-167 
#Pages 6 
Date of Issue 2022-06-08 (RCS) 

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