Master Thesis: Understanding Power Consumption Through Frequency-Time Grid Visualization

Join our Team

About this opportunity
How can we make future mobile networks more energy efficient and sustainable?

Energy consumption is one of the key challenges for 4G and 5G networks, and will continue to be critical as networks evolve towards 6G. At Ericsson, extensive work is ongoing to develop intelligent power-saving features that reduce energy usage while maintaining network performance. However, many of these features operate in a highly dynamic frequency-time domain that can be difficult to understand and visualize.

In this thesis, you will explore how radio resources are allocated across frequency and time, how this relates to power consumption, and how power-saving features influence network behavior. By developing intuitive visualizations, you will help transform complex and abstract concepts into something that can be analyzed, explained, and demonstrated. The results can support the development of more energy-efficient networks and contribute to reducing the environmental footprint of mobile communications.
What you will do

You will investigate the frequency-time domain in 4G and 5G systems and study how scheduling decisions and resource allocations affect power consumption. The work will focus on making Energy Performance features more understandable and actionable through visualization and analysis.

You will have freedom to define areas of exploration within the project. These could include, but are not limited to:

• Understanding the fundamentals of Energy Performance and power-saving features in 4G and 5G networks.
• Investigating how scheduling features utilize the frequency-time grid.
• Visualizing the allocation of Physical Resource Blocks (PRBs) across frequency and time.
• Connecting resource allocation patterns to power consumption.
• Developing visualization concepts that make complex Energy Performance features easier to understand and demonstrate.
• Identifying opportunities to improve existing frequency-time power features.
• Exploring how these visualizations can support future feature development and sustainability initiatives.

The skills you bring

• Knowledge in Computer Science, Electrical Engineering, Telecommunications, Physics, or a related field.
• Experience in at least one programming language.
• Interest in data analysis, visualization, and problem solving.
• Curiosity about wireless communication systems and sustainable technology.
• Eagerness to learn how modern mobile networks can reduce energy consumption while maintaining performance.
• Bonus: knowledge of 4G/5G systems, signal processing, data visualization, or machine learning.
• Bonus: experience in machine learning.