Master thesis - Energy-aware RAN and site infrastructure network enabled by AI ML
Ericsson
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About the Opportunity:
Ericsson is a world-leading provider of telecommunications equipment and services to mobile and fixed network operators. Over 1,000 networks in more than 180 countries use Ericsson equipment, and more than 40 percent of the world's mobile traffic passes through Ericsson networks. Using innovation to empower people, business and society, Ericsson is working towards the Networked Society: a world connected in real time that will open up opportunities to create freedom, transform society and drive solutions to some of our planet’s greatest challenges.
With the large deployments of 5G and future 6G, several high-performing radio sites are considered. Energy usage will be challenging for various deployments, both during operation and orchestration. There is a need to find solutions to operate and manage the radio sites efficiently, considering variable parameters, KPIs, as well as renewable energy sources
The demand is to apply AI/ML, including providing actionable recommendations within the network, without any impact or KPI degradations, while remaining sustainable from an end-to-end point of view.
What You Will Do:
- Consider the defined network deployments and predefined models
- Identify and propose optimization and recommendations that can be applied with the objective to lower energy usage from an end-to-end view.
The thesis would also involve the following steps (can be adjusted to research interest of the candidate):
- Literature review, identifying relevant concepts and algorithms for analysis and optimization of communication.
- Model and implement the technique for different scenarios of the selected proposal for best end-to-end optimization.
- Performance and evaluation of the RAN savings and infrastructure including alternative sources, with objective to enable low energy usage.
The Skills You Bring:
We are looking for 1 open-minded student who seeks challenging research work with the freedom to propose and develop own ideas. To be successful in this thesis work you would need the following:
- Currently pursuing a MSc degree in Computer Science, Electrical and Computer Engineering or similar areas.
- Excellent programming skills in Python.
- Good knowledge of concepts in machine learning (e.g. deep learning).
- Experiences with machine learning libraries Tensor flow, Keras, PyTorch, sci-kit learn etc.
- Experience with Docker/Kubernetes is a bonus.
- Be fluent 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 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: 772789