At a glance
- Opportunity
- Master's thesis
- Location
- Linköping, SE
- Funding / pay
- Not specified by the organization
- Eligibility
- Check the qualifications in the official posting
Project description
## Join our Team About this opportunity: Energy efficiency is a defining key performance indicator (KPI) for 6G. The radio access network (RAN) is a major part of a mobile network operator’s (MNO’s) energy use, and much of that energy is spent even at low traffic because the network is dimensioned for peak load. Many of the decisions that keep hardware active are taken at Layer 3 (L3) — the control plane — through radio resource control (RRC) connection states, admission control, and mobility. Today these mechanisms are mostly rule-based and tuned for performance, leaving energy-saving potential on the table. As 6G becomes AI-native, data-driven L3 control that jointly optimizes quality of service (QoS) and energy is a promising but challenging direction. What you will do: * Reduce network energy consumption through smarter L3 control while respecting QoS guarantees, and quantify the energy–performance trade-off. * Model how L3 decisions (RRC states, cell activation/sleep, admission control) map to network energy consumption using a system-level simulator. * Implement a rule-based baseline aligned with 3GPP standards and design energy-aware policies, including a reinforcement-learning policy that coordinates cell sleep with RRC. * Evaluate across load levels and produce energy–performance trade-off curves (e.g., watts per bit vs. latency, throughput, and SLA violations). * Conclude with recommendations for energy-aware 6G L3 design and a presentation of results. The skills you bring: * Master´s student in electrical engineering, computer science, or similar * Programming experience in Python (and/or C++, Rust) * Basic machine learning and/or reinforcement learning * Interest in 3GPP protocol layers (RRC/L3) * Strong teamwork skills; ideal for two students with a split focus: * One leaning toward protocols/systems * One leaning toward ML 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) || Linköping Req ID: 791412
Funding and compensation
Compensation not specified. See the original posting for amounts, duration and conditions.
Eligibility and application requirements
Review the qualifications, research interests and required documents in the description above. The employer or university's original posting is the source for complete eligibility requirements.
Before you apply
0 of 4 readyA preparation checklist, saved on this device. The official posting determines eligibility and required documents.
How to apply
Submit your application through Ericsson's official application process before 23 Mar 2027.
Source and listing information
This opportunity is published by Ericsson. Read the original official posting. Conditions and availability may change; confirm them with the organization. Availability verification refers to the source check, not organization endorsement.
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