| Paper Abstract and Keywords |
| Presentation |
2024-11-12 11:15
[Poster Presentation]
Micro-Signal Detection Method Using Deep Learning
Ayaka Sata, Shunsuke Uehashi, Yasutaka Yamashita, Satoshi Yoshima (Mitsubishi Electric) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
The detection of wireless signals is important as a key technology for identifying desired waves and understanding
the state of surrounding wireless communications in fields such as wireless communication systems and radio monitoring.
Conventionally, a method called power detection has been used, which determines the presence of a signal when the received
power exceeds a threshold relative to the noise level. However, power detection has the disadvantage of not being able to detect
low SNR signals. Therefore, in recent years, signal detection using deep learning has been considered. The method using deep
learning allows for signal detection by pre-training with the input as the time waveform of the signal and the output as the result
of signal presence (presence: 1, absence: 0). We compared the method using deep learning that we propose with the conventional
method of power detection and a method using one of the unsupervised machine learning techniques, ‘One-Class SVM,’
commonly used for anomaly detection through simulation. As a result, it was found that the proposed method could achieve a
90% accuracy rate at the lowest SNR, which is a 4dB improvement compared to the conventional method. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Signal Detection / Deep Learning / / / / / / |
| Reference Info. |
IEICE Tech. Rep. |
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| Download PDF |
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| Conference Information |
| Committee |
RISING |
| Conference Date |
2024-11-11 - 2024-11-12 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Kaderu 2・7 (Sapporo) |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Cross-Field Research Association of Super-Intelligent Networking |
| Paper Information |
| Registration To |
RISING |
| Conference Code |
2024-11-RISING |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Micro-Signal Detection Method Using Deep Learning |
| Sub Title (in English) |
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Signal Detection |
| Keyword(2) |
Deep Learning |
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| 1st Author's Name |
Ayaka Sata |
| 1st Author's Affiliation |
Mitsubishi Electric Corporation (Mitsubishi Electric) |
| 2nd Author's Name |
Shunsuke Uehashi |
| 2nd Author's Affiliation |
Mitsubishi Electric Corporation (Mitsubishi Electric) |
| 3rd Author's Name |
Yasutaka Yamashita |
| 3rd Author's Affiliation |
Mitsubishi Electric Corporation (Mitsubishi Electric) |
| 4th Author's Name |
Satoshi Yoshima |
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Mitsubishi Electric Corporation (Mitsubishi Electric) |
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| Speaker |
Author-1 |
| Date Time |
2024-11-12 11:15:00 |
| Presentation Time |
50 minutes |
| Registration for |
RISING |
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| Volume (vol) |
vol. |
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