Deep RP-CNN for Burst Signal Detection in Cognitive Radios
This article proposes a convolutional neural network (CNN)-based signal detection scheme using image encoding techniques for burst signals in wireless networks. The conventional signal detection approach based on energy measurement performs poorly when detecting burst signals owing to the short sign...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9194011/ |
| _version_ | 1818618565496930304 |
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| author | Dongho Seo Haewoon Nam |
| author_facet | Dongho Seo Haewoon Nam |
| author_sort | Dongho Seo |
| collection | DOAJ |
| description | This article proposes a convolutional neural network (CNN)-based signal detection scheme using image encoding techniques for burst signals in wireless networks. The conventional signal detection approach based on energy measurement performs poorly when detecting burst signals owing to the short signal length and relatively long sensing duration. To detect the presence of a burst signal, the proposed scheme encodes the received time-series signal into an image that is further fed to a CNN model. For image encoding techniques, recurrence plot algorithms are adopted in the proposed scheme with a CNN. In particular, the proposed scheme achieves the correct detection probability of 99% even in the presence of a short burst signal at SNR= -10 dB. |
| first_indexed | 2024-12-16T17:23:37Z |
| format | Article |
| id | doaj.art-96eed7b4787a478285db476d7f60da04 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:23:37Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-96eed7b4787a478285db476d7f60da042022-12-21T22:23:06ZengIEEEIEEE Access2169-35362020-01-01816716416717110.1109/ACCESS.2020.30232629194011Deep RP-CNN for Burst Signal Detection in Cognitive RadiosDongho Seo0https://orcid.org/0000-0002-3394-3422Haewoon Nam1https://orcid.org/0000-0001-9847-7023Division of Electrical Engineering, Hanyang University, Ansan, South KoreaDivision of Electrical Engineering, Hanyang University, Ansan, South KoreaThis article proposes a convolutional neural network (CNN)-based signal detection scheme using image encoding techniques for burst signals in wireless networks. The conventional signal detection approach based on energy measurement performs poorly when detecting burst signals owing to the short signal length and relatively long sensing duration. To detect the presence of a burst signal, the proposed scheme encodes the received time-series signal into an image that is further fed to a CNN model. For image encoding techniques, recurrence plot algorithms are adopted in the proposed scheme with a CNN. In particular, the proposed scheme achieves the correct detection probability of 99% even in the presence of a short burst signal at SNR= -10 dB.https://ieeexplore.ieee.org/document/9194011/Burst signal detectioncognitive radiodeep learningrecurrence plotenergy detection |
| spellingShingle | Dongho Seo Haewoon Nam Deep RP-CNN for Burst Signal Detection in Cognitive Radios IEEE Access Burst signal detection cognitive radio deep learning recurrence plot energy detection |
| title | Deep RP-CNN for Burst Signal Detection in Cognitive Radios |
| title_full | Deep RP-CNN for Burst Signal Detection in Cognitive Radios |
| title_fullStr | Deep RP-CNN for Burst Signal Detection in Cognitive Radios |
| title_full_unstemmed | Deep RP-CNN for Burst Signal Detection in Cognitive Radios |
| title_short | Deep RP-CNN for Burst Signal Detection in Cognitive Radios |
| title_sort | deep rp cnn for burst signal detection in cognitive radios |
| topic | Burst signal detection cognitive radio deep learning recurrence plot energy detection |
| url | https://ieeexplore.ieee.org/document/9194011/ |
| work_keys_str_mv | AT donghoseo deeprpcnnforburstsignaldetectionincognitiveradios AT haewoonnam deeprpcnnforburstsignaldetectionincognitiveradios |