Master's thesis; 5G testbed implementation and data generation

We have an open position for a master student to join us at the Connected Intelligence research unit, within the Computer Science department at RISE.

Background
Private 5G networks are becoming essential for industries that need reliable, low-latency, and secure connectivity. Machine learning models are increasingly used in these networks to predict KPIs and support automated decision-making. Training robust models, however, depends on having high-quality data that captures diverse, realistic, and challenging operating conditions. Because of that, designing the right experiments, collecting detailed measurements, and building well-curated datasets for 5G use cases is now seen as a core contribution in the telecom as well as the machine learning community.

Description
This thesis focuses on building and analyzing a private 5G network testbed. You will study 5G base station hardware, deploy both RAN and core network components using open-source software, and design experiments to collect real network data. You will then perform initial analysis of this data using statistical methods to understand system behavior and performance. You will also evaluate basic ML models for KPI prediction on the generated datasets. There is also an opportunity to contribute to open source by releasing curated datasets from the testbed.

Expected skills

• Programming skills in Python and C++

• Basic knowledge of wireless/telecom networks

• Experience working with SDRs or network traffic generators is a plus

Terms

• Start time: as soon as possible.

• Scope: 30 hp (20 weeks)

• Location: RISE, Stockholm (Kista). Options to partially work remotely.

• Compensation: In line with RISE guidelines we offer 40,000 SEK for a completed thesis of high quality

Welcome with your application!
To know more, please contact Akhila Rao (akhila.rao@ri.se). Applications should include a CV, recent grades, and a code example if possible. Candidates are encouraged to send in their application as soon as possible but at the latest by the 5th of December 2025. Suitable applicants will be interviewed as soon as applications are received.