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  11. Channel Code-book (ccb): Semantic Image-adaptive Transmission In Satellite-ground Scenario.
  1. Home
  3. Research Domains
  5. Engineering
  7. Communications Engineering
  9. Satellite Communications
  11. Channel Code-book (ccb): Semantic Image-adaptive Transmission In Satellite-ground Scenario.

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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

View abstract on PubMed

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.