Performance Analysis for Multi-layer Unmanned Aerial Vehicle Networks

TL;DR

This paper models and analyzes multi-layer UAV networks, deriving key probabilistic metrics, and identifies optimal UAV heights and densities to maximize successful transmission probability.

Contribution

It introduces a comprehensive probabilistic model for multilayer UAV networks considering LoS/NLoS channels and derives bounds for optimal UAV deployment parameters.

Findings

Existence of an optimal UAV height for network performance.

Upper bounds for UAV density decrease with increased UAV height.

Derived probability distribution functions for link distances and interference.

Abstract

In this paper, we provide the model of the multilayer aerial network (MAN), composed unmanned aerial vehicles (UAVs) that distributed in Poisson point process (PPP) with different densities, heights, and transmission power. In our model, we consider the line of sight (LoS) and non-line of sight (NLoS) channels which is probabilistically formed. We firstly derive the probability distribution function (PDF) of the main link distance and the Laplace transform of interference of MAN considering strongest average received power-based association. We then analyze the successful transmission probability (STP) of the MAN and provide the upper bound of the optimal density that maximizes the STP of the MAN. Through the numerical results, we show the existence of the optimal height of UAV due to a performance tradeoff caused by the height of the aerial network (AN), and also show the upper bounds of the optimal densities in terms of the STP, which decrease with the height of the ANs.