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Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite-Ground Scenario.

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Summary
This summary is machine-generated.

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.

Keywords:
channel adaptiveimage transmissionsatellite–ground scenariossemantic communication

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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.