Job
- Level
- Junior
- Job Feld
- Software
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Ort
- München
- Arbeitsmodell
- Onsite
Job Zusammenfassung
In dieser Position entwickelst du präzise Modelle zur Durchsatzkapazität von Wi-Fi-Kanälen, berücksichtigst Umwelteinflüsse und baust eine Architektur für inkrementelles Lernen zur Anpassung an dynamische Szenarien.
Job Technologien
Deine Rolle im Team
- 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.
Unsere Erwartungen an dich
Qualifikationen
- 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.
- Must be eligible to work in the European Union to be considered for this position.
- Fluent in English (written and oral).
Erfahrung
- 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.
Unser Angebot
- 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.
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Huawei
Als weltweit führender Anbieter von Informations- und Kommunikationstechnologie (IKT) - Lösungen ist Huawei bestrebt, durch kontinuierliche Innovationen und offene Zusammenarbeit Wettbewerbsvorteile zu erzielen. Unsere IKT-Produktpalette umfasst End-to-End-Lösungen für Telekommunikations- und Unternehmensnetze sowie Cloud Computing-, Device- und Service-Technologien.
Description
- Sprachen
- Englisch
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Onsite
- Branche
- Elektronik, Automatisation, Internet, IT, Telekom
Master student for Wi-Fi throughput capacity modeling
- Ort
- München
- Arbeitsmodell
- Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
