About the Opportunity

Massive MIMO is a key enabling technology for 5G and improvements in massive MIMO will be a key factor in overall capacity and coverage enhancements of wireless networks. Lot of efforts are being made by 3GPP and wireless device vendors around massive MIMO. Multiple types of massive MIMO schemes are already possible to choose from. These MIMO schemes will have their own merits and demerits from performance perspective and their performance also depends on the wireless channel condition. Even the complexity of different MIMO schemes will be different and needs to be considered before selecting a MIMO scheme for a given wireless channel condition.

What You Will Do

In this thesis you will explore data analysis and machine learning techniques to reduce the massive MIMO complexity. The thesis requires collection of real time data and analysis of these data to explore MIMO simplification. Summary of thesis is given below,
• Complexity analysis: Understanding of the growing complexity of base stations and different types of MIMO schemes.
• AI/Machine learning: Explore machine learning techniques to reduce massive MIMO complexity.
• Data analysis: Understand different types of data that is available at the base station and their usage. Participate in real time data collection and data analysis.
• Develop machine learning model to simplify the MIMO scheme with help of collected data and analysis.
• Documentation: Prepare detailed documentation of your findings

The Skills You Bring

• Master’s degree in computer science, computer engineering, Electrical engineering or similar
• Skills in AI, machine learning and data analysis
• Excellent communication and collaboration skills with good fluency in 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