Mode of Employment: Limited
Use your knowledge as a springboard.
Industrial use cases require deterministic wireless connectivity. A promising base technology to fulfill these requirements is OFDMA-based Wi-Fi (i.e.Wi-Fi 6 and beyond) with advantages such as scalability, flexibility and mobility compared to wired networking solutions. However, current Wi-Fi mechanisms, as defined in the 802.11 standard, are not suited for industrial use cases due to their probabilistic channel access mechanisms. Shaping future Wi-Fi solutions to cope with the demanding industrial requirements is an exciting direction for upcoming research. The scope of this master thesis is on deterministic communication using wireless technologies. More specifically, the focus is on predictable channel access mechanisms in OFDMA-based Wi-Fi.
Change the future with us.
- You will analyze related literature and state of the art on channel access mechanisms in Wi-Fi 6/7 and beyond
- You will derive and define concepts and mechanisms for guaranteed channel access
- You will evaluate the proposed concepts based on network simulations using the ns3 framework
- You will compare different channel access mechanisms regarding their performance
What you need to make real what matters.
- You are currently pursuing a Master’s degree in electrical engineering, information or computer science (or similar course of studies) with strong background on network architectures and protocols, communication systems or real-time communication
- You have a profound knowledge on current wireless standards and protocols and keen interest in Wi-Fi networks (Wi-Fi 6/7)
- Knowledge of Wi-Fi’s MAC layer would be beneficial
- You have practical experience in C++ programming
- Knowledge in using current network simulation frameworks (like ns3 or OMNet++) would be desirable
- You have experience in working with Linux and no fear of bash and CLIs
- You bring very good written and spoken English or German skills
Make your mark in our exciting world at Siemens.
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Company: Siemens AG
Experience Level: Student (Not Yet Graduated)
Full / Part time: Either