| IEICE Technical Committee Submission System Conference Paper's Information |
Online Proceedings [Sign in] Tech. Rep. Archives |
| Go Top Page | Go Previous | [Japanese] / [English] |
| Paper Abstract and Keywords | ||
| Presentation | 2023-10-19 13:00 [Poster Presentation] A Proposal of Indoor Radio Propagation Prediction Method by using DCNN Masamitsu Irikuchi, Teturo Imai (TDU), Koshiro Kitao, Satoshi Suyama (DOCOMO)  AP2023-119 |
|
| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In the next generation communication system (6G), where further improvement of frequency utilization efficiency and power efficiency is an issue, a highly accurate radio propagation estimation method is required for system and area design. A propagation loss estimation method based on Deep Convolutional Neural Networks (DCNN) is currently under investigation. However, the effectiveness of this method for indoor environments has not been clarified because the previous studies were conducted in outdoor environments. In this paper, we propose a DCNN-based propagation loss estimation method and evaluate its accuracy using a simple indoor model. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Deep learning / Indoor environment / Radio propagation / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 223, AP2023-119, pp. 115-116, Oct. 2023. | |
| Paper # | AP2023-119 | |
| Date of Issue | 2023-10-12 (AP) | |
| 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 | AP2023-119 |
|
| Conference Information | |
| Committee | AP |
| Conference Date | 2023-10-19 - 2023-10-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Iwate University |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Student Session, Antennas and Propagation |
| Paper Information | |
| Registration To | AP |
| Conference Code | 2023-10-AP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Proposal of Indoor Radio Propagation Prediction Method by using DCNN |
| Sub Title (in English) | |
| Keyword(1) | Deep learning |
| Keyword(2) | Indoor environment |
| Keyword(3) | Radio propagation |
| Keyword(4) | |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Masamitsu Irikuchi |
| 1st Author's Affiliation | Tokyo Denki University (TDU) |
| 2nd Author's Name | Teturo Imai |
| 2nd Author's Affiliation | Tokyo Denki University (TDU) |
| 3rd Author's Name | Koshiro Kitao |
| 3rd Author's Affiliation | NTT DOCOMO (DOCOMO) |
| 4th Author's Name | Satoshi Suyama |
| 4th Author's Affiliation | NTT DOCOMO (DOCOMO) |
| 5th Author's Name | |
| 5th Author's Affiliation | () |
| 6th Author's Name | |
| 6th Author's Affiliation | () |
| 7th Author's Name | |
| 7th Author's Affiliation | () |
| 8th Author's Name | |
| 8th Author's Affiliation | () |
| 9th Author's Name | |
| 9th Author's Affiliation | () |
| 10th Author's Name | |
| 10th Author's Affiliation | () |
| 11th Author's Name | |
| 11th Author's Affiliation | () |
| 12th Author's Name | |
| 12th Author's Affiliation | () |
| 13th Author's Name | |
| 13th Author's Affiliation | () |
| 14th Author's Name | |
| 14th Author's Affiliation | () |
| 15th Author's Name | |
| 15th Author's Affiliation | () |
| 16th Author's Name | |
| 16th Author's Affiliation | () |
| 17th Author's Name | |
| 17th Author's Affiliation | () |
| 18th Author's Name | |
| 18th Author's Affiliation | () |
| Speaker | Author-1 |
| Date Time | 2023-10-19 13:00:00 |
| Presentation Time | 120 minutes |
| Registration for | AP |
| Paper # | AP2023-119 |
| Volume (vol) | vol.123 |
| Number (no) | no.223 |
| Page | pp.115-116 |
| #Pages | 2 |
| Date of Issue | 2023-10-12 (AP) |
[Return to Top Page]