Coverage Maximization for a Poisson Field of Drone Cells

TL;DR

This paper analyzes how drone base station parameters like antenna pattern, altitude, and density affect coverage probability, providing optimization insights for aerial wireless networks with height-dependent channel models.

Contribution

It introduces a comprehensive model for drone-based networks considering height-dependent shadowing and antenna patterns, deriving optimal system parameters for coverage maximization.

Findings

Optimal drone altitude and density for maximum coverage.

A simplified LoS probability model effective up to 500 meters.

Characterization of interference in dynamic drone networks.

Abstract

The use of drone base stations to provide wireless connectivity for ground terminals is becoming a promising part of future technologies. The design of such aerial networks is however different compared to cellular 2D networks, as antennas from the drones are looking down, and the channel model becomes height-dependent. In this paper, we study the effect of antenna patterns and height-dependent shadowing. We consider a random network topology to capture the effect of dynamic changes of the flying base stations. First we characterize the aggregate interference imposed by the co-channel neighboring drones. Then we derive the link coverage probability between a ground user and its associated drone base station. The result is used to obtain the optimum system parameters in terms of drones antenna beamwidth, density and altitude. We also derive the average LoS probability of the associated drone and show that it is a good approximation and simplification of the coverage probability in low altitudes up to 500 m according to the required signal-to-interference-plus-noise ratio (SINR).