Dense satellite constellations recently emerged as a prominent solution to complementing terrestrial networks in attaining true global coverage. As such, analytic optimization techniques can be adopted to rapidly maximize the benefits of such satellite networks. The paper presents a framework that relies on two primary tuning parameters to optimize the uplink performance; (i) the constellation altitude and (ii) the satellite antenna beamwidth. The framework leverages tools from stochastic geometry to derive analytical models that formulate a parametric uplink coverage problem which also includes user traffic demand as an input. This allows operators to devise uplink expansion strategies to cater for expanding user demand. The framework demonstrates that fine-tuning of these parameters can significantly enhance the network capacity. We show that the optimization of random constellations provides a close match to that of practical satellite constellations such as Walker-delta and Walker-star.

翻译：因此,可采用分析优化技术,以迅速使这类卫星网络的惠益最大化。文件提出了一个框架,依靠两个主要的调整参数来优化上行链路性能;(一) 星座高度和(二) 卫星天线的束线。框架利用从随机几何学获得的工具来得出分析模型,以形成一个参数上行链路覆盖问题,其中也包括用户流量需求,作为投入。该框架使运营商能够设计扩大战略,以满足用户需求的扩大。框架表明这些参数的微调可以大大增强网络能力。我们显示,随机星座的优化与沃克-德尔塔和沃克-斯塔斯塔尔等实用卫星星座的优化非常接近。