Master student for on-system throughput capacity modeling of Wi-Fi communication channels

Huawei Heisenberg Research Center (Munich) is responsible for advanced technology research, architectural development, design and strategic engineering of our products.

The Optical and Quantum Communications Laboratory in Munich researches and develops signal processing, components and systems for fixed access, data center networks, metro and long-haul optical networks. The department engages in local research and collaborates with academic and industrial partners from the European ecosystem.

Join us as a

Master student for on-system throughput capacity modeling of Wi-Fi communication channels (m/f/d)

Your mission

• Develop accurate and efficient models for throughput capacity of Wi-Fi communication channels, addressing the fact that measured throughput can vary by more than 30% due to environmental factors and interference, and that current packet-based probing mechanisms achieve below 50% accuracy in dynamic scenarios
• Design an online incremental training and learning architecture capable of handling diverse access points and stations, varied building layouts (wall penetration, multipath reflection), environmental changes, and interference — the vast number of possible combinations necessitates online adaptation rather than static pre-computation
• Investigate the limitations of current channel information acquisition under Wi-Fi standard protocols and chip design constraints, including Null Data
• Address MIMO transmission constraints
• Validate the solution through simulation based on Huawei-specified protocols and use cases, followed by verification on Huawei's actual use cases

Your areas of expertise

• Student in Electrical, Electronic, Communications Engineering, Computer Science, or related fields
• Knowledge of wireless communication systems, particularly Wi-Fi (IEEE 802.11ax/be) PHY and MAC layer concepts (OFDM, MIMO, channel sounding, NDP, CSI feedback, link adaptation)
• Understanding of throughput analysis and channel capacity fundamentals, including the impact of MCS, channel bandwidth, spatial streams, and packet aggregation on effective throughput
• Good programming skills in at least Python or C/C++ or industry-standard simulation tools
• Experience with machine learning frameworks (e.g., scikit-learn, PyTorch, TensorFlow) and online/incremental learning techniques
• Experience with network simulation tools (such as NS3, OMNeT++, etc.) is a plus
• Must be eligible to work in the European Union to be considered for this position
• Fluent in English (written and oral)

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• Your rewards of working here

• Our culture is characterized by innovative power and team spirit as well as the intensive exchange of knowledge and experience within our global network.
• We offer healthy meals ranging from traditional Chinese to western delicacies in our famous company canteen.
• To keep your development ongoing, you will find a broad range of training opportunities. Many online and face-to-face training programs incl. language courses in German and Mandarin.
• Our diverse and welcoming environment is shaped by different backgrounds and around 40 individual nationalities.
• Self-responsible work in a competent, motivated and constantly growing team.

Please send your application and CV (incl. cover letter and reference letters) in English.

Huawei is a leading global information and communications technology (ICT) solutions provider. Our ICT solutions, products and services are used in more than 170 countries and regions, serving over one-third of the world's population. With 208,000 employees, Huawei is committed to develop the future information society and build a Better Connected World.