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Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite-Ground Scenario
Hui Cao1, Shujun Han1, Rui Meng1
1State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Sensors (Basel, Switzerland)
|January 11, 2025
Summary
This study introduces a Channel Code-Book (CCB) semantic communication (SemCom) model for adaptive satellite image transmission. The CCB model enhances efficiency and accuracy in diverse, changing channel conditions.
Area of Science:
- Satellite Communications
- Information Theory
- Signal Processing
Background:
- Satellite-ground communication is vital for global systems but faces efficiency challenges due to rapid satellite movement and channel variations.
- Semantic communication (SemCom) offers improved transmission efficiency by conveying information meaning, ideal for satellite image transmission.
- Existing SemCom methods lack adaptability to dynamic channel conditions.
Purpose of the Study:
- To propose an adaptive SemCom transmission model for satellite image transmission in varied channel environments.
- To enhance the robustness and efficiency of SemCom technology against channel fluctuations.
Main Methods:
- Developed a Channel Code-Book (CCB) based SemCom model for adaptive image transmission.
- The model documents fading and noise states to reconstruct and restore images.
- Dynamically adjusted denoiser model parameters based on channel conditions.
Main Results:
- The proposed CCB model demonstrated superior performance compared to Deep JSCC, ASCN, and WITT.
- Achieved over 10 dB advantage under high signal-to-noise ratio conditions.
- The model effectively adapts to diverse channel environments and task conditions.
Conclusions:
- The CCB-based SemCom model offers a robust solution for adaptive satellite image transmission.
- This approach significantly improves transmission efficiency and image quality in challenging satellite communication scenarios.
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