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Comprehensive Simulation Framework for Space-Air-Ground Integrated Network Propagation Channel Research.

Zekai Zhang1, Shaoyang Song2,3, Jingzehua Xu1

  • 1Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
Summary

This study introduces a simulation framework for space-air-ground integrated network (SAGIN) propagation channel research, addressing real-world data challenges. The framework enables efficient channel simulation and scenario identification using AI algorithms.

Keywords:
QuaDRiGapropagation channel researchsatellite channel simulation platformscenario identificationspace–air–ground integrated network

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Area of Science:

  • Wireless Communication
  • Network Engineering
  • Signal Processing

Background:

  • Space-air-ground integrated networks (SAGIN) are crucial for next-generation mobile communications, offering reliable and adaptable coverage.
  • Propagation channel research is vital for SAGIN system design and resource management.
  • Real-world propagation channel research faces significant hurdles in data collection, deployment, and testing.

Purpose of the Study:

  • To design a comprehensive simulation framework to overcome challenges in SAGIN propagation channel research.
  • To facilitate the simulation of communication channels across diverse scenarios within SAGIN.
  • To integrate data processing, intelligent identification, and algorithm optimization for simulated data analysis.

Main Methods:

  • Integration of the open-source QuaDRiGa platform with a self-developed satellite channel simulation platform.
  • Modular integration of data processing, intelligent identification, and algorithm optimization modules.
  • Extraction of typical channel features from channel impulse response (CIR) data for scenario identification.

Main Results:

  • A functional simulation framework for SAGIN propagation channel research was developed.
  • Demonstration of scenario identification through feature extraction and AI-based model comparison.
  • Successful simulation of communication channels across various integrated network scenarios.

Conclusions:

  • The proposed simulation framework effectively addresses the limitations of real-world data collection in SAGIN propagation channel research.
  • The integrated approach allows for robust channel simulation and intelligent analysis of propagation characteristics.
  • The study provides a valuable tool for advancing SAGIN network design and resource deployment through simulated channel insights.