Modulation classification analysis of CNN model for wireless communication systems
Modulation classification (MC) is a critical task in wireless communication systems, enabling the identification of the modulation class in the received signals. In this paper, we analyzed a novel multi-layer convolutional neural network (CNN) to extract hierarchical features directly from the raw b...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-10-01
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| Series: | AIMS Electronics and Electrical Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/electreng.2023018?viewType=HTML |
| _version_ | 1797367611212693504 |
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| author | Tamizhelakkiya K Sabitha Gauni Prabhu Chandhar |
| author_facet | Tamizhelakkiya K Sabitha Gauni Prabhu Chandhar |
| author_sort | Tamizhelakkiya K |
| collection | DOAJ |
| description | Modulation classification (MC) is a critical task in wireless communication systems, enabling the identification of the modulation class in the received signals. In this paper, we analyzed a novel multi-layer convolutional neural network (CNN) to extract hierarchical features directly from the raw baseband samples. Moreover, we compared the training and testing accuracy of the CNN model for various decimation rates, input sample size and the number of convolutional layers. The results showed that the three-layer CNN model provided better classification accuracy with less computation cost. Furthermore, we observed that the MC performance of the proposed CNN model was better than the other deep learning (DL) and cumulant-based models. |
| first_indexed | 2024-03-08T17:20:49Z |
| format | Article |
| id | doaj.art-6c3e87316d5d438f8cc99c89dbc9efe4 |
| institution | Directory Open Access Journal |
| issn | 2578-1588 |
| language | English |
| last_indexed | 2024-03-08T17:20:49Z |
| publishDate | 2023-10-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Electronics and Electrical Engineering |
| spelling | doaj.art-6c3e87316d5d438f8cc99c89dbc9efe42024-01-03T05:44:12ZengAIMS PressAIMS Electronics and Electrical Engineering2578-15882023-10-017433735310.3934/electreng.2023018Modulation classification analysis of CNN model for wireless communication systemsTamizhelakkiya K0Sabitha Gauni 1Prabhu Chandhar21. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, Tamil Nadu, India3. Chandhar Research Labs Pvt Ltd, Chennai, Tamil Nadu, India1. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, Tamil Nadu, India 2. Autosys Control Systems India Pvt Ltd, Chennai, Tamil Nadu, India3. Chandhar Research Labs Pvt Ltd, Chennai, Tamil Nadu, IndiaModulation classification (MC) is a critical task in wireless communication systems, enabling the identification of the modulation class in the received signals. In this paper, we analyzed a novel multi-layer convolutional neural network (CNN) to extract hierarchical features directly from the raw baseband samples. Moreover, we compared the training and testing accuracy of the CNN model for various decimation rates, input sample size and the number of convolutional layers. The results showed that the three-layer CNN model provided better classification accuracy with less computation cost. Furthermore, we observed that the MC performance of the proposed CNN model was better than the other deep learning (DL) and cumulant-based models.https://www.aimspress.com/article/doi/10.3934/electreng.2023018?viewType=HTMLmodulation classification (mc)cnndeep learning (dl)feature mapneural network |
| spellingShingle | Tamizhelakkiya K Sabitha Gauni Prabhu Chandhar Modulation classification analysis of CNN model for wireless communication systems AIMS Electronics and Electrical Engineering modulation classification (mc) cnn deep learning (dl) feature map neural network |
| title | Modulation classification analysis of CNN model for wireless communication systems |
| title_full | Modulation classification analysis of CNN model for wireless communication systems |
| title_fullStr | Modulation classification analysis of CNN model for wireless communication systems |
| title_full_unstemmed | Modulation classification analysis of CNN model for wireless communication systems |
| title_short | Modulation classification analysis of CNN model for wireless communication systems |
| title_sort | modulation classification analysis of cnn model for wireless communication systems |
| topic | modulation classification (mc) cnn deep learning (dl) feature map neural network |
| url | https://www.aimspress.com/article/doi/10.3934/electreng.2023018?viewType=HTML |
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