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| Presentation | 2020-07-16 11:20 User Identification and Channel Estimation by Iterative DNN-Based Decoder on Multiple-Access Fading Channel Lantian Wei, Shan Lu, Hiroshi Kamabe (Gifu Univ.), Jun Cheng (Doshisha Univ.)  IT2020-12 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The user identification scheme for multiple-access fading channel based on the random generated (0,1,-1)-signature code is considered. In the previous works, the signature code was used over a noisy multiple-access adder channel and only the status of uses are decoded by the signature decoder. In this paper, by considering the communication model as a compressed sensing process, it is possible to estimate the channel coefficients while identifying users. To improve the efficiency of the decoding process, we proposed an iterative deep-neural-network(DNN)-based decoder. Our simulation results show that for the random generated (0,1,-1)-signature code, our proposed DNN-based decoder requires less computing time to achieve higher active user detection accuracy and channel estimation accuracy than the classical signal recovery algorithm used in compressed sensing. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | signature code / deep neural network / compressed sensing / user identification / channel estimation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 105, IT2020-12, pp. 7-12, July 2020. | |
| Paper # | IT2020-12 | |
| Date of Issue | 2020-07-09 (IT) | |
| 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 | IT2020-12 |
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| Conference Information | |
| Committee | IT |
| Conference Date | 2020-07-16 - 2020-07-16 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Freshman session, General |
| Paper Information | |
| Registration To | IT |
| Conference Code | 2020-07-IT |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | User Identification and Channel Estimation by Iterative DNN-Based Decoder on Multiple-Access Fading Channel |
| Sub Title (in English) | |
| Keyword(1) | signature code |
| Keyword(2) | deep neural network |
| Keyword(3) | compressed sensing |
| Keyword(4) | user identification |
| Keyword(5) | channel estimation |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Lantian Wei |
| 1st Author's Affiliation | Gifu University (Gifu Univ.) |
| 2nd Author's Name | Shan Lu |
| 2nd Author's Affiliation | Gifu University (Gifu Univ.) |
| 3rd Author's Name | Hiroshi Kamabe |
| 3rd Author's Affiliation | Gifu University (Gifu Univ.) |
| 4th Author's Name | Jun Cheng |
| 4th Author's Affiliation | Doshisha University (Doshisha Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-07-16 11:20:00 |
| Presentation Time | 25 minutes |
| Registration for | IT |
| Paper # | IT2020-12 |
| Volume (vol) | vol.120 |
| Number (no) | no.105 |
| Page | pp.7-12 |
| #Pages | 6 |
| Date of Issue | 2020-07-09 (IT) |
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