| Paper Abstract and Keywords |
| Presentation |
2021-09-03 13:35
Convolutional Radio Modulation Recognition Networks with Attention Models in Wireless Systems
Haohui Jia, Na Chen, Minoru Okada (NAIST) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In modern wireless systems, deep learning (DL) shows promising performance for wireless signal processing. DL model driven communication system is able to recognize the class of modulation signals as a DL training process, such as convolutional neural network (CNN), without any expert knowledge of underlying channel models. However, the performance of radio recognition based on CNN architecture is sensitive, unreliable and slow training convergence due to the noise interference. In this paper, we introduce a learned attention model into the radio domain for modulation recognition by employing the transformer networks and CNN-based pretreatment to extract the premier feature as input of transformer networks. This attention model allows the network to focus on the characteristics of the radio signal itself without expert knowledge of the signal structure for classification. Using this architecture, we develop a highly reliable modulation recognition under the low signal to noise ratio (SNR) over the wireless communication system. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Wireless Communication / Deep Learning / Convolutional Neural Network / Self-attention / Transformer / / / |
| Reference Info. |
ITE Tech. Rep., vol. 45, no. 24, BCT2021-35, pp. 1-4, Sept. 2021. |
| Paper # |
BCT2021-35 |
| Date of Issue |
2021-08-27 (BCT) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
|
| Conference Information |
| Committee |
BCT IEEE-BT |
| Conference Date |
2021-09-03 - 2021-09-03 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Online |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Mobile systems, etc |
| Paper Information |
| Registration To |
BCT |
| Conference Code |
2021-09-BCT-BT |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Convolutional Radio Modulation Recognition Networks with Attention Models in Wireless Systems |
| Sub Title (in English) |
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| Keyword(1) |
Wireless Communication |
| Keyword(2) |
Deep Learning |
| Keyword(3) |
Convolutional Neural Network |
| Keyword(4) |
Self-attention |
| Keyword(5) |
Transformer |
| Keyword(6) |
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| 1st Author's Name |
Haohui Jia |
| 1st Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
| 2nd Author's Name |
Na Chen |
| 2nd Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
| 3rd Author's Name |
Minoru Okada |
| 3rd Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
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| Speaker |
Author-1 |
| Date Time |
2021-09-03 13:35:00 |
| Presentation Time |
20 minutes |
| Registration for |
BCT |
| Paper # |
BCT2021-35 |
| Volume (vol) |
vol.45 |
| Number (no) |
no.24 |
| Page |
pp.1-4 |
| #Pages |
4 |
| Date of Issue |
2021-08-27 (BCT) |