Bachelor Thesis: AI-Assisted Rx Selection for 6G MIMO

## Join our Team

About this opportunity:

In modern mobile networks, the UE receiver must handle increasingly complex signal conditions especially when a base station transmits to multiple users simultaneously (MU-MIMO). Different receiver algorithms excel under different radio conditions, but knowing which one to use and when remains an open question in 3GPP standardization.

This thesis will investigate when advanced receivers (R-ML) outperform conventional ones (MMSE-IRC) for 5G/6G MIMO demodulation, and whether a simple AI classifier can learn to predict the better choice from observable radio parameters. You will use a physical layer simulator to generate data, analyze performance tradeoffs, and train a data-driven decision model.

What you will do:

• Study two MIMO receiver algorithms MMSE-IRC and R-ML to understand their strengths, limitations, and computational tradeoffs.
• Learn to run physical layer simulations using a Python-based simulator tool.
• Design and execute a structured simulation campaign comparing MMSE-IRC and R-ML across a range of conditions: SNR levels, channel models, and UE speeds. Then Analyze the results.
• Train a simple classifier that predicts the better receiver from easily observable radio parameters such as SNR, channel type, and Doppler spread.
• Visualize the findings through throughput curves, heatmaps, and decision boundaries that can be used in technical reports.
• Document your work.

The skills you bring:

• You are pursuing a B.Sc. in Engineering Mathematics or Computer Science.
• You have a solid foundation in Python and are comfortable with data analysis libraries (pandas, numpy, matplotlib).
• You have taken an introductory course in machine learning and understand basic concepts like classification, decision trees, and cross-validation.
• You have basic signal processing knowledge, understanding concepts like MIMO at a conceptual level.
• You are curious about wireless communications and interested in exploring how AI/ML can be applied to radio network problems.
• You can work both independently and as part of a pair, and communicate results clearly in written and spoken English.

Why join Ericsson?At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

What happens once you apply?Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.

Primary country and city: Sweden (SE) || Stockholm

Req ID: 793418