Modulation recognition method based on multi-inputs convolution neural network
In order to identify the main modulation modes adopted in current satellite communication systems,a signal modulation recognition algorithm based on multi-inputs convolution neural network was proposed.With the prior information of the signals and knowledge of the network topological structure,the t...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2019-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2019206/ |
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| _version_ | 1841539364536975360 |
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| author | Xiong ZHA Hua PENG Xin QIN Guang LI Tianyun LI |
| author_facet | Xiong ZHA Hua PENG Xin QIN Guang LI Tianyun LI |
| author_sort | Xiong ZHA |
| collection | DOAJ |
| description | In order to identify the main modulation modes adopted in current satellite communication systems,a signal modulation recognition algorithm based on multi-inputs convolution neural network was proposed.With the prior information of the signals and knowledge of the network topological structure,the time-domain signal waveforms were converted into eye diagrams and vector diagrams to represent the shallow features of the signals.Meanwhile,the modulation recognition model based on multi-inputs convolution neural network was designed.Through the training of the network,the shallow features were deeply extracted and mapped.Finally,the signal modulation recognition task was completed.The simulation results show that compared with the traditional algorithms and deep learning algorithms,the proposed method has a better anti-noise performance,and the overall recognition rate of this algorithm can reach 95% when the signal-to-noise ratio is 5 dB. |
| format | Article |
| id | doaj-art-939fdf5abccd4985ab6b74a4d625e02d |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2019-11-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-939fdf5abccd4985ab6b74a4d625e02d2025-01-14T07:18:09ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2019-11-0140303759731770Modulation recognition method based on multi-inputs convolution neural networkXiong ZHAHua PENGXin QINGuang LITianyun LIIn order to identify the main modulation modes adopted in current satellite communication systems,a signal modulation recognition algorithm based on multi-inputs convolution neural network was proposed.With the prior information of the signals and knowledge of the network topological structure,the time-domain signal waveforms were converted into eye diagrams and vector diagrams to represent the shallow features of the signals.Meanwhile,the modulation recognition model based on multi-inputs convolution neural network was designed.Through the training of the network,the shallow features were deeply extracted and mapped.Finally,the signal modulation recognition task was completed.The simulation results show that compared with the traditional algorithms and deep learning algorithms,the proposed method has a better anti-noise performance,and the overall recognition rate of this algorithm can reach 95% when the signal-to-noise ratio is 5 dB.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2019206/modulation recognitionmulti-inputs convolution neural networkeye diagramvector diagram |
| spellingShingle | Xiong ZHA Hua PENG Xin QIN Guang LI Tianyun LI Modulation recognition method based on multi-inputs convolution neural network Tongxin xuebao modulation recognition multi-inputs convolution neural network eye diagram vector diagram |
| title | Modulation recognition method based on multi-inputs convolution neural network |
| title_full | Modulation recognition method based on multi-inputs convolution neural network |
| title_fullStr | Modulation recognition method based on multi-inputs convolution neural network |
| title_full_unstemmed | Modulation recognition method based on multi-inputs convolution neural network |
| title_short | Modulation recognition method based on multi-inputs convolution neural network |
| title_sort | modulation recognition method based on multi inputs convolution neural network |
| topic | modulation recognition multi-inputs convolution neural network eye diagram vector diagram |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2019206/ |
| work_keys_str_mv | AT xiongzha modulationrecognitionmethodbasedonmultiinputsconvolutionneuralnetwork AT huapeng modulationrecognitionmethodbasedonmultiinputsconvolutionneuralnetwork AT xinqin modulationrecognitionmethodbasedonmultiinputsconvolutionneuralnetwork AT guangli modulationrecognitionmethodbasedonmultiinputsconvolutionneuralnetwork AT tianyunli modulationrecognitionmethodbasedonmultiinputsconvolutionneuralnetwork |