Join Ericsson for a master’s thesis investigating how neural-network-based AI receivers can adapt to changing wireless conditions in live radio access networks. You will explore unsupervised and self-supervised online adaptation strategies that enable a physical shared channel (PxSCH) receiver to maintain performance across varying configurations and propagation environments without requiring labeled training data.
You will review research on online learning, self-supervised training, and domain adaptation for AI receivers. Using field-trial data, you will analyze how receiver performance changes across different PxSCH configurations and channel conditions and identify the causes of performance degradation. You will then design, implement, and evaluate one or more online adaptation methods against a static baseline. The evaluation will consider receiver accuracy, link-level performance such as BLER and throughput, adaptation speed, computational cost, and model stability. The thesis will conclude with a presentation of your results and recommendations to the Ericsson research team.
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: 791257
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