Paper Abstract and Keywords |
Presentation |
2022-01-20 10:55
Rate-compatible LDPC Code in Dynamic Environment based on Reinforcement Learning Li Zizhen, Shan Lu, Hiroshi Kamabe (Gifu Univ.) IT2021-35 SIP2021-43 RCS2021-203 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
To balance the time delay caused by switching code rates and the system performance, we proposed a code rate switching algorithm in the dynamic communication environment based on reinforcement learning to increase the average transmission rate. We define a Markov Decision Process (MDP) and create a Q-table (as policy) that represents the expectation of the future reward for performing an action (R) under a particular state (SNR, R). Then, a proposed reinforcement learning algorithm is developed to find the optimal selection of coding rate. The simulation result shows that the proposed system significantly improved the transmission rate while satisfying the system performance requirement. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Reinforcement Learning / LDPC code / Rate-compatible / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 327, IT2021-35, pp. 40-44, Jan. 2022. |
Paper # |
IT2021-35 |
Date of Issue |
2022-01-13 (IT, SIP, 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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IT2021-35 SIP2021-43 RCS2021-203 |
Conference Information |
Committee |
RCS SIP IT |
Conference Date |
2022-01-20 - 2022-01-21 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
IT |
Conference Code |
2022-01-RCS-SIP-IT |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Rate-compatible LDPC Code in Dynamic Environment based on Reinforcement Learning |
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Reinforcement Learning |
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LDPC code |
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Rate-compatible |
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1st Author's Name |
Li Zizhen |
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 |
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Gifu University (Gifu Univ.) |
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Speaker |
Author-1 |
Date Time |
2022-01-20 10:55:00 |
Presentation Time |
25 minutes |
Registration for |
IT |
Paper # |
IT2021-35, SIP2021-43, RCS2021-203 |
Volume (vol) |
vol.121 |
Number (no) |
no.327(IT), no.328(SIP), no.329(RCS) |
Page |
pp.40-44 |
#Pages |
5 |
Date of Issue |
2022-01-13 (IT, SIP, RCS) |
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