Paper Details
Abstract
This study presents a Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) system aimed at improving the offloading capabilities of clustered Internet of Things (IoT) networks. A single UAV collects computation-intensive tasks from IoT Devices (IDs) using uplink Non-Orthogonal Multiple Access (NOMA), with wireless channels modeled by Nakagami-m fading to capture realistic propagation effects. The focus is on deriving a closed-form expression for the Offloading Outage Probability (OOP), which measures the likelihood that tasks are successfully offloaded from IDs to the UAV. A circular UAV trajectory is considered, and simulation results are provided to validate the analysis and evaluate how key parameters, such as device density, UAV altitude, and channel conditions, influence the OOP.