Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground Scenario
Satellite–ground communication is a critical component in the global communication system, significantly contributing to environmental monitoring, radio and television broadcasting, aerospace operations, and other domains. However, the technology encounters challenges in data transmission efficiency...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/1/269 |
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| author | Hui Cao Shujun Han Rui Meng Xiaodong Xu Ping Zhang |
| author_facet | Hui Cao Shujun Han Rui Meng Xiaodong Xu Ping Zhang |
| author_sort | Hui Cao |
| collection | DOAJ |
| description | Satellite–ground communication is a critical component in the global communication system, significantly contributing to environmental monitoring, radio and television broadcasting, aerospace operations, and other domains. However, the technology encounters challenges in data transmission efficiency, due to the drastic alterations in the communication channel caused by the rapid movement of satellites. In comparison to traditional transmission methods, semantic communication (SemCom) technology enhances transmission efficiency by comprehending and leveraging the intrinsic meaning of information, making it ideal for image transmission in satellite communications. Nevertheless, current SemCom methods still struggle to adapt to varying channel conditions. To address this, we propose a SemCom transmission model based on a Channel Code-Book (CCB) for adaptive image transmission in diverse channel environments. Our model reconstructs and restores the original image by documenting fading and noise states under various channel conditions and dynamically adjusting the denoiser’s model parameters. Extensive experimental results demonstrate that our CCB model outperforms three representative baseline models, including Deep JSCC, ASCN, and WITT in various environments and task conditions, achieving an advantage of more than 10 dB under high signal-to-noise ratio conditions. |
| format | Article |
| id | doaj-art-f71d947a8ca444eab0c30307c93c12c4 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-f71d947a8ca444eab0c30307c93c12c42025-01-10T13:21:25ZengMDPI AGSensors1424-82202025-01-0125126910.3390/s25010269Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground ScenarioHui Cao0Shujun Han1Rui Meng2Xiaodong Xu3Ping Zhang4State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSatellite–ground communication is a critical component in the global communication system, significantly contributing to environmental monitoring, radio and television broadcasting, aerospace operations, and other domains. However, the technology encounters challenges in data transmission efficiency, due to the drastic alterations in the communication channel caused by the rapid movement of satellites. In comparison to traditional transmission methods, semantic communication (SemCom) technology enhances transmission efficiency by comprehending and leveraging the intrinsic meaning of information, making it ideal for image transmission in satellite communications. Nevertheless, current SemCom methods still struggle to adapt to varying channel conditions. To address this, we propose a SemCom transmission model based on a Channel Code-Book (CCB) for adaptive image transmission in diverse channel environments. Our model reconstructs and restores the original image by documenting fading and noise states under various channel conditions and dynamically adjusting the denoiser’s model parameters. Extensive experimental results demonstrate that our CCB model outperforms three representative baseline models, including Deep JSCC, ASCN, and WITT in various environments and task conditions, achieving an advantage of more than 10 dB under high signal-to-noise ratio conditions.https://www.mdpi.com/1424-8220/25/1/269semantic communicationsatellite–ground scenarioschannel adaptiveimage transmission |
| spellingShingle | Hui Cao Shujun Han Rui Meng Xiaodong Xu Ping Zhang Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground Scenario Sensors semantic communication satellite–ground scenarios channel adaptive image transmission |
| title | Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground Scenario |
| title_full | Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground Scenario |
| title_fullStr | Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground Scenario |
| title_full_unstemmed | Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground Scenario |
| title_short | Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite–Ground Scenario |
| title_sort | channel code book ccb semantic image adaptive transmission in satellite ground scenario |
| topic | semantic communication satellite–ground scenarios channel adaptive image transmission |
| url | https://www.mdpi.com/1424-8220/25/1/269 |
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