基于细粒度随机几何的低地轨道卫星通信系统分析

Yanshi Sun;Zhiguo Ding
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摘要

最近,随机几何被用于为低地球轨道(LEO)卫星网络提供可行的性能分析。然而,现有研究主要侧重于分析 "覆盖概率",提供的信息有限。为了提供更多洞察力,本文对以同质泊松点过程(HPPP)建模的低地球轨道卫星网络进行了更精细的分析。具体而言,研究了给定点过程的条件覆盖概率分布和矩。所得出的分析结果可为低地球轨道卫星网络提供 "用户公平性 "和 "多大程度的用户能达到给定的传输可靠性 "等现有文献中没有的特征。仿真结果可验证上述分析。数值结果表明,在密集的卫星网络中,在低空部署卫星有利于提高覆盖概率和用户公平性。
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A Fine Grained Stochastic Geometry-Based Analysis on LEO Satellite Communication Systems
Recently, stochastic geometry has been applied to provide tractable performance analysis for low earth orbit (LEO) satellite networks. However, existing works mainly focus on analyzing the “coverage probability”, which provides limited information. To provide more insights, this letter provides a more fine grained analysis on LEO satellite networks modeled by a homogeneous Poisson point process (HPPP). Specifically, the distribution and moments of the conditional coverage probability given the point process are studied. The developed analytical results can provide characterizations on LEO satellite networks, which are not available in existing literature, such as “user fairness” and “what fraction of users can achieve a given transmission reliability”. Simulation results are provided to verify the developed analysis. Numerical results show that, in a dense satellite network, it is beneficial to deploy satellites at low altitude, for the sake of both coverage probability and user fairness.
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Table of Contents IEEE Networking Letters Author Guidelines IEEE COMMUNICATIONS SOCIETY IEEE Communications Society Optimal Classifier for an ML-Assisted Resource Allocation in Wireless Communications
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