Paper Abstract and Keywords |
Presentation |
2021-06-23 09:40
A Comparison of Variational Bayesian and Expectation Propagation Methods for Massive MIMO Signal Detection Hiroki Asumi, Junichiro Hagiwara, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, Takanori Sato (Hokkaido Univ.) RCS2021-30 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Signal detection in massive MIMO has difficulty in reducing computational complexity as the number of antennas increases.It is well known that naive application of maximum likelihood decoding causes unrealistic complexity.This report studies the applicability of the stochastic variational Bayesian method as an approach to reduce computational complexity.While the variational Bayesian method approximates the target distribution by minimizing the Kullback-Leibler divergence, the existing expectation propagation method can also be interpreted similarly.We have compared the detection performance and computational complexity between both methods.As a result, we have found that the variational Bayesian method achieves better detection performance in many cases than the expectation propagation method with a polynomial order complexity, while it is computationally more expensive than the expectation propagation method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Massive MIMO / Signal Detection / Expectation Propagation Method / Variational Bayesian Method / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 72, RCS2021-30, pp. 7-12, June 2021. |
Paper # |
RCS2021-30 |
Date of Issue |
2021-06-16 (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) |
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RCS2021-30 |
Conference Information |
Committee |
RCS |
Conference Date |
2021-06-23 - 2021-06-25 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
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 |
2021-06-RCS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Comparison of Variational Bayesian and Expectation Propagation Methods for Massive MIMO Signal Detection |
Sub Title (in English) |
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Keyword(1) |
Massive MIMO |
Keyword(2) |
Signal Detection |
Keyword(3) |
Expectation Propagation Method |
Keyword(4) |
Variational Bayesian Method |
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1st Author's Name |
Hiroki Asumi |
1st Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
2nd Author's Name |
Junichiro Hagiwara |
2nd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
3rd Author's Name |
Toshihiko Nishimura |
3rd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
4th Author's Name |
Takeo Ohgane |
4th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
5th Author's Name |
Yasutaka Ogawa |
5th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
6th Author's Name |
Takanori Sato |
6th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
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Speaker |
Author-1 |
Date Time |
2021-06-23 09:40:00 |
Presentation Time |
10 minutes |
Registration for |
RCS |
Paper # |
RCS2021-30 |
Volume (vol) |
vol.121 |
Number (no) |
no.72 |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2021-06-16 (RCS) |
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