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<p>The increasing density of Low-Earth Orbit (LEO) satellite constellations presents significant challenges in spectrum management, particularly for weak signal perception under interference. To solve the problem of poor perception ability and insufficient spectrum resources for weak signals, a task driven array enhancement and spectrum sensing based collaborative optimization sharing system for low orbit satellites and synchronous Earth orbit is proposed. The optimization of weak signal perception is enhanced by a dual-feedback random phase optimization algorithm, while variables such as perception time and transmission power are optimized through collaborative optimization sharing algorithm. In the simulation experiment, the dual-feedback random phase optimization algorithm achieves convergence at a time gap of about 20 milliseconds, and the final signal to interference noise ratio (SINR) converges to around 8.98. The collaborative optimization sharing algorithm achieves the maximum throughput when the maximum threshold value is -128, with a value of 3.82. Finally, the collaborative optimization sharing algorithm achieves a time utilization rate of 82% even when the interference effect is strongest, demonstrating its robustness and efficiency in contested spectrum environments. The results indicate that the algorithm established by the research can effectively improve the perception ability of weak signals and achieve higher throughput and time utilization. This work provides a robust framework for dynamic spectrum sharing that enhances the operational efficiency and reliability of next-generation LEO satellite systems.</p>

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Enhanced spectrum sharing for multi-satellite low-orbit arrays through task-driven collaborative optimization

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月15日

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  • Jieliang Zheng,
  • Qiang Lv,
  • Fenghua Xu,
  • Yukun Zhu,
  • Yu Chen

摘要

The increasing density of Low-Earth Orbit (LEO) satellite constellations presents significant challenges in spectrum management, particularly for weak signal perception under interference. To solve the problem of poor perception ability and insufficient spectrum resources for weak signals, a task driven array enhancement and spectrum sensing based collaborative optimization sharing system for low orbit satellites and synchronous Earth orbit is proposed. The optimization of weak signal perception is enhanced by a dual-feedback random phase optimization algorithm, while variables such as perception time and transmission power are optimized through collaborative optimization sharing algorithm. In the simulation experiment, the dual-feedback random phase optimization algorithm achieves convergence at a time gap of about 20 milliseconds, and the final signal to interference noise ratio (SINR) converges to around 8.98. The collaborative optimization sharing algorithm achieves the maximum throughput when the maximum threshold value is -128, with a value of 3.82. Finally, the collaborative optimization sharing algorithm achieves a time utilization rate of 82% even when the interference effect is strongest, demonstrating its robustness and efficiency in contested spectrum environments. The results indicate that the algorithm established by the research can effectively improve the perception ability of weak signals and achieve higher throughput and time utilization. This work provides a robust framework for dynamic spectrum sharing that enhances the operational efficiency and reliability of next-generation LEO satellite systems.