Thesis (Master) - Sidelink-based radio resource allocation for Cooperative Robotics

Mode of Employment: Fixed Term

Are you ready to shape the future of cooperative robotics? Join us in Garching for your Master Thesis on Sidelink-based radio resource allocation for Cooperative Robotics and dive deep into groundbreaking research on ultra-reliable, low-latency wireless communication—your innovation could set new standards for tomorrow’s smart factories!

What We Offer You

• Exciting research and development projects that put your theoretical knowledge into practice
• Individual supervision and support from experienced experts in your field
• Access to the latest technologies, laboratories, and resources
• Diverse opportunities to contribute your ideas and actively shape the projects
• Excellent career opportunities through contact with potential employers

You'll make an impact by

• You begin by analytically characterizing the incompatibility between the standard 3GPP Rel.16 Mode 2 autonomous resource selection procedure and sub-millisecond URLLC requirements in cooperative robotic Sidelink scenarios, using modeling and/or simulation in NS-3
• Building on this, you investigate lightweight and instantaneous channel observation mechanisms as alternatives to the standard multi-millisecond sensing window, evaluating their feasibility and accuracy in dynamic factory channel conditions
• One possible path could be to investigate neuromorphic computing approaches - in particular event-driven neural network architectures such as Spiking Neural Networks (SNNs) - as a candidate inference engine for MAC-layer resource selection, with focus on inference latency feasibility within the available PDB budget of 1-3 ms
• Finally, you benchmark the proposed mechanisms against the standard 3GPP Rel.16 Mode 2 baseline in terms of resource selection latency and reliability under TS 22.104, and assess their scalability for cooperative robot pairs (unicast) and small groups (groupcast) within a factory deployment area

This Is How You'll Win Us Over

• Education: You are currently enrolled in a degree program in Electrical Engineering, Computer Science, or a related field with a focus on wireless communications
• Experience and Skills:
• You possess advanced programming skills in Python and C/C++
• You have knowledge of the structure and operation of wireless communication systems such as LTE, 5G, or NR-V2X
• Experience with radio resource allocation algorithms and tools such as Open Air Interface, NS3 5G-LENA, Keras, Tensorflow, or Pytorch is beneficial
• Ways of Working: You work independently, analytically, and demonstrate a high level of commitment and initiative
• Languages: You have very good English skills

You are much more than your qualifications, and we believe in the potential of every single candidate. We look forward to getting to know you!

At Siemens, we believe that feeling valued and included is the foundation for doing great work. That’s why we aim to create an inclusive workplace where everyone feels a sense of belonging, and where individual perspectives and experiences are celebrated. Our commitment to fairness and respect extends to every applicant.

As an equal opportunity employer, we welcome applications from individuals of all backgrounds and particularly encourage applications from persons with disabilities.

About Us

The world never stands still. And new challenges arise every day. With a passion for questioning things, for supplying ideas, and intelligently driving things forward we are helping society move towards a smarter tomorrow. Be it with technologies that reduce carbon emissions in cities or hyperintelligent robots. This is how we are able, to tackle the most important projects and push them forward together. Help us shape the future.

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