Master’s Thesis Discusses the Use of Cognitive Radio Networks for Unmanned Aerial Vehicles at the Faculty of Computer Science and Mathematics.

The Department of Computer Science at the Faculty of Computer Science and Mathematics discussed a master’s thesis titled “Using Cognitive Radio Network to Connect Drones”. This thesis, authored by Hashem Ali Hashem, aims to compare several navigation models for Unmanned Aerial Vehicles (UAVs) that utilize cellular networks. The study focuses on obtaining service from Unmanned Aircraft Base Stations (DBSs) for User Equipment (UE) located on the ground. Four distinct navigation models are explored: Random Waypoint (RWP), Straight Line (SL), Random Stop (RS), and Random Walk (RW). The SL navigation model is inspired by simulation models used by the Third Generation Partnership Project (3GPP) for UAV positioning and trajectory. On the other hand, RWP, RS, and RW are well-known mobility models that strike a balance between realism and tractability. The study investigates two service models: the UE-Dependent Model (UDM) and the UE-Independent Model (UIM). The primary contribution of this research lies in developing a comprehensive technique for analyzing point processes at Unmanned Aircraft Base Stations (DBSs) in various navigation models and services. The thesis has been successfully accepted