Fundamentals of Drone Cellular Network Analysis under Random Waypoint Mobility Model

TL;DR

This paper provides the first stochastic geometry-based analysis of drone cellular networks with drones moving according to a random waypoint model, assessing interference and performance over time.

Contribution

It introduces a novel analytical framework for drone networks with RWP mobility, including simplified models and performance metrics.

Findings

Characterizes interference field for mobile drone base stations.

Analyzes average user rate as a function of drone mobility.

First to analyze drone networks with RWP mobility on an infinite plane.

Abstract

In this paper, we present the first stochastic geometry-based performance analysis of a drone cellular network in which drone base stations (DBSs) are initially distributed based on a Poisson point process (PPP) and move according to a random waypoint (RWP) mobility model. The serving DBS for a typical user equipment (UE) on the ground is selected based on the nearest neighbor association policy. We further assume two service models for the serving DBS: (i) UE independent model (UIM), and (ii) UE dependent model (UDM). All the other DBSs are considered as interfering DBSs for the typical UE. We introduce a simplified RWP (SRWP) mobility model to describe the movement of interfering DBSs and characterize its key distributional properties that are required for our analysis. Building on these results, we analyze the interference field as seen by the typical UE for both the UIM and the UDM using displacement theorem, which forms the basis for characterizing the average rate at the typical UE as a function of time. To the best of our knowledge, this is the first work that analyzes the performance of a mobile drone network in which the drones follow an RWP mobility model on an infinite plane.