A-Level Mini-Projects

The research team has been running projects for Exeter Mathematics School A-level students since 2018. These projects are designed to challenge the students, and give them an insight into the research methods used in our Lab. 

In each project, the students learn the basics of the digital 5G infrastructure, and then solve a particular problem relating to network slicing and digital twin technology. At the end of the project, they present their work in the form of a report and a public presentation. Read more about each project below:

Project 1: Mathematical modelling and optimization for network routing in 5G

In this project, the students are tasked to create a computer routing model, to understand how information is sent around a telecommunications network to different destinations. To do this, they learn about and use a mathematical tool called “combinatorial optimization”, which helps to find the optimal (shortest, fastest) path through the network. 

The students then test and improve their model to work efficiently even when uncertainties are present. A real 5G network has lots of uncertainties, such as: how many users will need the system at once, what are their service requirements,… So, this project is a good introduction to the technical challenges of making a 5G network.

Project 2: Resource optimization of network slicing in 5G

This is a mini-project related to our research in 5G network slicing, most suitable for students who are already familiar with programming languages. The students start by learning about the principles of 5G, network slicing, machine learning and AI techniques.

The students then have the challenge of putting all this together, to first create a network slicing model, and then use DRL to use the network resources most effectively. This is an opportunity for students to try out a multidisciplinary research challenge; using techniques from artificial intelligence and applying it to telecommunications networks.

Project 3: Artificial Intelligence-based Digital Twin Models for Network Management

This mini-project is related to our work in designing digital twins, most suitable for students with programming experience and an interest in neural networks (used in machine learning). The students start with building their understanding of how a digital twin models the physical network, and also learning about the different types of neural networks.

The students then choose their preferred neural network to help create a digital twin that learns from historical data, makes predictions and tries to optimise the allocation of resources. This is the most challenging project we run, particularly interesting for students who would like a deep understanding of machine learning techniques.