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| Presentation | 2022-06-16 14:55 A study on model parameters for MIMO signal detection using learned AMP Mari Miyoshi, Toshihiko Nishimura, Takanori Sato, Takeo Ohgane, Yasutaka Ogawa, Junichiro Hagiwara (Hokkaido Univ.)  RCS2022-50 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Approximate message passing (AMP) is applicable to massive MIMO signal detection and achieves a high detection performance with low computational complexity. However, when two conditions required by AMP, i.e., the large system limit and a property that each entry of the channel matrix follows an independent and identically distributed complex Gaussian distribution, are not satisfied, the detection performance is severely degraded. It has been found that the degradation is relaxed by introducing a constant multiplier to the observation rate which is the ratio of the numbers of received to transmitted signals. The optimal value of the multiplier depends on the numbers of transmit and receive antennas, signal-to-noise ratio, and other conditions. Learned AMP (LAMP) , which is based on deep unfolding, can perform signal detection while optimizing the multiplier, and has high detection performance. In this paper, we compare the model parameters used for learning. It is found that modification to residual interference power is needed for proper learning when model parameters based on the strict AMP algorithm are used. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | MIMO / approximate message passing / deep learning / deep unfolding / spatial correlation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 73, RCS2022-50, pp. 156-161, June 2022. | |
| Paper # | RCS2022-50 | |
| 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 | RCS2022-50 |
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| 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 model parameters for MIMO signal detection using learned AMP |
| Sub Title (in English) | |
| Keyword(1) | MIMO |
| Keyword(2) | approximate message passing |
| Keyword(3) | deep learning |
| Keyword(4) | deep unfolding |
| Keyword(5) | spatial correlation |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Mari Miyoshi |
| 1st Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 2nd Author's Name | Toshihiko Nishimura |
| 2nd Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 3rd Author's Name | Takanori Sato |
| 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 | Junichiro Hagiwara |
| 6th Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-06-16 14:55:00 |
| Presentation Time | 25 minutes |
| Registration for | RCS |
| Paper # | RCS2022-50 |
| Volume (vol) | vol.122 |
| Number (no) | no.73 |
| Page | pp.156-161 |
| #Pages | 6 |
| Date of Issue | 2022-06-08 (RCS) |
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