About this opportunity:
Ericsson has identified positioning as a key use case for cellular networks. For wide area networks, mobile network operators are mandated to support positioning to accommodate emergency services like 112. For indoor local areas like factory environments, there is strong interest to have positioning accuracy with 1 meter error which can enable important industrial use cases, e.g., navigation of AGVs (Automated Guided Vehicles).
AI/ML (Artificial Intelligence/Machine Learning) in the domain of radio based cellular positioning is a fast emerging technology showing significant improvements over traditional positioning solutions.
What you will do:
This thesis is divided into several steps with the end goal of showing simulation results of positioning accuracy and reliability of an AI/ML algorithms in various positioning use cases in an industrial factory scenario. Main aspect to evaluate is how non-ideal antenna patterns on the device side impacts performance of AI/ML based positioning. With non-ideal antenna patterns the horizontal rotation of the device will impact the positioning performance.
The following steps are envisioned as part of the thesis work:
Implement at least one AI/ML algorithm for positioning and test using an advanced simulation environment. Compare performance between AI/ML based positioning and rule based positioning (legacy methods).Compare performance between an AI/ML model trained with ideal antenna patterns and evaluated with realistic antenna patterns on the device side.Compare performance between an AI/ML model trained with realistic antenna patterns and evaluated with realistic antenna patterns on the device side. Vary the number of device rotation angles in the training set and evaluate how different training sets impacts the positioning performance.
The thesis will be concluded with a report and a presentation for the Ericsson Standard & Technology team.
The skills you bring:
This project aims at students in electrical engineering, computer science, computer engineering or similar. Background in wireless communication and interest in AI/ML research is preferred.
Extent:
2 students, 30hp each
Location:
Lund, Sweden
Preferred Starting Date:
January 20, 2025
Keywords (if applicable):
Mobile Telecommunication, Cellular, Positioning, AI/ML, Matlab, Omniverse
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) || Lund
Req ID: 756669