Theses
M.Sc. Theses Proposals

Study of cloud radio access network and edge computing in High-Altitude Platforms and nanosatellites

Co-Advisor: Riccardo Bassoli (TU Dresden) - GOAL: to design and simulate technologies for cloud radio access network and edge computing for HAPs

Self-aware Softwarized Networks

Implementing and running the digital twin of a network (automated topology identification, sync)

Throughput, delay and jitter measurement in a 5G virtualized network environment

GOAL: to deploy a container-based architecture to perform KPI measurements in a 5G Service Based Architecture scenario

Energy-aware multi-access edge cloud

GOAL: to define algorithms capable of enabling energy-aware MEC operation, e.g. in presence of renewable energy sources

Evaluating the energy consumption of a virtualized infrastructure

GOAL: to build a framework for analyzing the energy consumption of a virtualized infrastructure

Measurements of Clock Drifts in Federated Networks

VICOMTECH, Spain

Federation of SDR and Virtualized Core Networks

VICOMTECH, Spain

Security-as-a-Service

Monokee/Athesys

Performance Evaluations of Orchestration Policies for Edge/Fog systems

Prof. Francesco De Pellegrini (Univ. of Avignon, France)

Network optimization using a Network Digital Twin

GOAL: to apply AI/ML to a simulated copy of a "real network" using the concept of Network Digital Twin.

Performance Evaluation of 5G/6G using a 3D engine and ray tracing propagation module

GOAL: to generate a 3D model of a city area and to emulate communications via ray tracing

A study on energy-efficient O-RAN deployment

Rawlings Ntassah, GOAL: The goal of this project is to analyze an energy-efficient way of deploying and managing the O-RAN.

xApps for slice orchestration and management in the O-RAN architecture

Rawlings Ntassah, GOAL: To develop an xApp for RAN slicing and resource allocation

AI/ML techniques for RAN management

Rawlings Ntassah, GOAL: The goal is to develop AI/ML techniques to optimize RAN functionality for closed-loop RAN management.

Video communications using semantic concepts and object recognition

GOAL: to develop a system for video communications based on semantic concepts provided by YOLO software for object recognition

Network Digital Twin and GPT

GOAL: to use GPT approaches in order to interpret the state and traffic flows of the Physical Twin and understand how to transfer the information to the Network Digital Twin

LLMs for intent based networking

GOAL: to use properly trained LLMs for understanding the intent of the network manager and the applications and define policies to optimize the network configuration

Digital Twinning of Networks and Drones

GOAL: to design and develop functionalities to define effective Digital Twins of UAVs and communication networks