# Modeling and Analysis of Data Harvesting Architecture based on Unmanned Aerial Vehicles

## TL;DR

This paper models a UAV-based IoT data harvesting system, analyzing its performance and deriving formulas for data upload, revealing trade-offs and optimal scheduling for maximizing network harvesting capacity.

## Contribution

It introduces a joint stationary model for UAVs and IoT devices, providing analytical insights into interference, coverage, and data harvesting capabilities.

## Key findings

- Linear relationship between UAV coverage and harvesting capacity
- Existence of an optimal IoT scheduling window
- Trade-off between data upload and scheduling window size

## Abstract

This paper explores an emerging wireless Internet-of-things (IoT) architecture based on unmanned aerial vehicles (UAVs). We consider a network where a fleet of UAVs at a fixed altitude flies on planned trajectories and IoT devices on the ground are scheduled to transmit their data to the UAVs when the latter are nearby. In such a system, the UAVs' motion triggers the uplink transmissions of the IoT devices. As a result, network performance is determined by the geometric and dynamic characteristics of the system. We propose a joint stationary model for UAVs and IoT devices and then evaluate the interference, the coverage probability, and the data rate of the typical UAV. To assess the harvesting capability of the proposed architecture, we derive a formula for the amount of data uploaded from each IoT device to a UAV. We also establish a linear relationship between the UAV coverage and the harvesting capability of the network, which provides insights into the design of the proposed harvesting scheme. In addition, we use our analytical results to numerically show that there exists a trade-off between the uploaded data and the size of the IoT scheduling window. Specifically, for a given UAV and IoT geometry, there exists an optimal scheduling window that maximizes the harvesting capability of the proposed network.