Presentation | 2022-01-20 Automatic Modulation Classification Based on SNR estimation using Multi-Task Learning Wataru Machida, Yosuke Sugiura, Nozomiko Yasui, Tetsuya Shimamura, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Automatic modulation classification is a technology that identifies the modulation type used in received signals and plays an important role in wireless communication. The purpose of this study is to improve the accuracy of the automatic modulation classification model by using multi-task learning architecture with two input formats, which are I/Q sample and A/P sample. Based on the conventional model, we propose a new model solving an auxiliary task of SNR estimation and incorporating an Attention mechanism. From the results of the evaluation experiment, we confirm that the proposed method can improve the accuracy of the automatic modulation classification. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Automatic modulation classification / Multi-task learning / SNR estimation / Attention Mechanism |
Paper # | IT2021-56,SIP2021-64,RCS2021-224 |
Date of Issue | 2022-01-13 (IT, SIP, RCS) |
Conference Information | |
Committee | RCS / SIP / IT |
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Conference Date | 2022/1/20(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Online |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Eiji Okamoto(Nagoya Inst. of Tech.) / Yukihiro Bandou(NTT) / Tadashi Wadayama(Nagoya Inst. of Tech.) |
Vice Chair | Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) / Fumihide Kojima(NICT) / Toshihisa Tanaka(Tokyo Univ. Agri.&Tech.) / Takayuki Nakachi(Ryukyu Univ.) / Tetsuya Kojima(Tokyo Kosen) |
Secretary | Toshihiko Nishimura(NEC) / Tomoya Tandai(Panasonic) / Fumihide Kojima(Xiaomi) / Toshihisa Tanaka(Takushoku Univ.) / Takayuki Nakachi(Tokyo Univ. Agri.&Tech.) / Tetsuya Kojima(Saitamai Univ.) |
Assistant | Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) / Taichi Yoshida(UEC) / Seisuke Kyochi(Univ. of Kitakyushu) / Masanori Hirotomo(Saga Univ.) |
Paper Information | |
Registration To | Technical Committee on Radio Communication Systems / Technical Committee on Signal Processing / Technical Committee on Information Theory |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Automatic Modulation Classification Based on SNR estimation using Multi-Task Learning |
Sub Title (in English) | |
Keyword(1) | Automatic modulation classification |
Keyword(2) | Multi-task learning |
Keyword(3) | SNR estimation |
Keyword(4) | Attention Mechanism |
1st Author's Name | Wataru Machida |
1st Author's Affiliation | Saitama University(Saitama Univ.) |
2nd Author's Name | Yosuke Sugiura |
2nd Author's Affiliation | Saitama University(Saitama Univ.) |
3rd Author's Name | Nozomiko Yasui |
3rd Author's Affiliation | Saitama University(Saitama Univ.) |
4th Author's Name | Tetsuya Shimamura |
4th Author's Affiliation | Saitama University(Saitama Univ.) |
Date | 2022-01-20 |
Paper # | IT2021-56,SIP2021-64,RCS2021-224 |
Volume (vol) | vol.121 |
Number (no) | IT-327,SIP-328,RCS-329 |
Page | pp.pp.155-160(IT), pp.155-160(SIP), pp.155-160(RCS), |
#Pages | 6 |
Date of Issue | 2022-01-13 (IT, SIP, RCS) |