Optimal Beamwidth and Altitude for Maximal Uplink Coverage in Satellite Networks

TL;DR

This paper introduces an analytical framework using stochastic geometry to optimize satellite constellation altitude and antenna beamwidth, significantly improving uplink coverage and capacity in satellite networks.

Contribution

It presents a novel optimization framework for satellite uplink performance based on key parameters, applicable to various constellation types.

Findings

Optimizing altitude and beamwidth enhances network capacity.

The framework closely matches practical constellation performance.

Parameter tuning significantly improves uplink coverage.

Abstract

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.