| Presentation | 2021-05-21 An evaluation of CNN using Deep Residual Learning for OFDM and Single Carrier Modulation Classification Teruji Ide, Rozeha A Rashid, Leon Chin, M A Sarijari, Rubita Sudirman, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this study, we investigate and present a deep residual learning for modulation classification. The simulation results show the degradation problem that was exposed due to an increase in network depth and the saturation of accuracy in the modified conventional CNN; however, the proposed CNN has no such degradation. Therefore, the processing burden of the conventional CNN is much larger than the proposed CNN. In the simulation results, the proposed CNN framework achieves almost the same modulation classification accuracy as the normal CNN framework when reducing the processing burden in the proposed one. The better simulation results are shown by adjustment of the parameters using the proposed method in the case of OFDM and single carrier modulation types. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | CNNcognitive radioresidual learningmodulation classification |
| Paper # | SR2021-9 |
| Date of Issue | 2021-05-13 (SR) |
| Conference Information | |
| Committee | SR |
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| Conference Date | 2021/5/20(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Software Radio, Machine Learning for Wireless Communication, etc. |
| Chair | Masayuki Ariyoshi(NEC) |
| Vice Chair | Suguru Kameda(Tohoku Univ.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) |
| Secretary | Suguru Kameda(ATR) / Osamu Takyu(Univ. of Electro-Comm.) / Kentaro Ishidu(Mie Univ.) |
| Assistant | Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Kentaro Kobayashi(Nagoya Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Smart Radio |
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| Language | ENG-JTITLE |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An evaluation of CNN using Deep Residual Learning for OFDM and Single Carrier Modulation Classification |
| Sub Title (in English) | |
| Keyword(1) | CNNcognitive radioresidual learningmodulation classification |
| 1st Author's Name | Teruji Ide |
| 1st Author's Affiliation | National Institute of Technology, Kagoshima College(NIT, Kagoshima College) |
| 2nd Author's Name | Rozeha A Rashid |
| 2nd Author's Affiliation | Universiti Teknologi Malaysia(UTM) |
| 3rd Author's Name | Leon Chin |
| 3rd Author's Affiliation | Universiti Teknologi Malaysia(UTM) |
| 4th Author's Name | M A Sarijari |
| 4th Author's Affiliation | Universiti Teknologi Malaysia(UTM) |
| 5th Author's Name | Rubita Sudirman |
| 5th Author's Affiliation | Universiti Teknologi Malaysia(UTM) |
| Date | 2021-05-21 |
| Paper # | SR2021-9 |
| Volume (vol) | vol.121 |
| Number (no) | SR-30 |
| Page | pp.pp.57-64(SR), |
| #Pages | 8 |
| Date of Issue | 2021-05-13 (SR) |