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arXiv 2409.04002cs.ITeess.SPmath.IT
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低地球轨道卫星网络分析:距离相关阴影下的覆盖

Low-Earth Orbit Satellite Network Analysis: Coverage under Distance-Dependent Shadowing

Jinseok Choi, Jeonghun Park, Junse Lee, Namyoon Lee

AI总结:

本文基于PPP网络框架分析最强卫星关联下的LEO卫星覆盖,推导覆盖概率及上下界与闭式解,揭示距离相关阴影和最优卫星高度的设计意义。

摘要:

本文采用最强卫星关联方法,对低地球轨道(LEO)卫星网络的覆盖性能进行了全面分析,特别强调通过基于泊松点过程(PPP)的网络框架建模的阴影效应。我们推导了覆盖概率的解析表达式,该表达式纳入关键系统参数和距离相关的阴影概率函数,并显式考虑视距和非视距传播信道。为提高研究结果的实际相关性,我们给出了覆盖概率的下界和上界,并引入基于简化阴影模型的闭式解。我们的分析揭示了若干重要的网络设计洞见,包括距离相关阴影效应可提升覆盖概率,以及识别出在波束增益收益与干扰弊端之间取得平衡的最优卫星高度。值得注意的是,我们基于PPP的网络模型与其他成熟模型高度一致,证实了其在多种卫星网络配置下的准确性和适用性。从分析中获得的洞见对于优化LEO卫星部署策略以及在多样化场景中提升网络性能具有重要价值。

英文摘要:

This paper offers a thorough analysis of the coverage performance of Low Earth Orbit (LEO) satellite networks using a strongest satellite association approach, with a particular emphasis on shadowing effects modeled through a Poisson point process (PPP)-based network framework. We derive an analytical expression for the coverage probability, which incorporates key system parameters and a distance-dependent shadowing probability function, explicitly accounting for both line-of-sight and non-line-of-sight propagation channels. To enhance the practical relevance of our findings, we provide both lower and upper bounds for the coverage probability and introduce a closed-form solution based on a simplified shadowing model. Our analysis reveals several important network design insights, including the enhancement of coverage probability by distance-dependent shadowing effects and the identification of an optimal satellite altitude that balances beam gain benefits with interference drawbacks. Notably, our PPP-based network model shows strong alignment with other established models, confirming its accuracy and applicability across a variety of satellite network configurations. The insights gained from our analysis are valuable for optimizing LEO satellite deployment strategies and improving network performance in diverse scenarios.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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