Explainable and Trustworthy AI/ML for 6G and Beyond (Next-G)

Institutions

  • TU Berlin
  • Fraunhofer HHI
  • Huawei

Team @ TKN

  • Osman Tugay Başaran (PI)
  • Prof. Dr. Falko Dressler
  • Dr. Götz-Philip Brasche (Huawei, CTO Cloud Europe)
  • Dr. Xun Xiao (Huawei, Principal Researcher @Advanced Wireless Technology Lab)
  • Dr. Xueli An (Huawei, Head of 6G Network Architecture Research Group)
  • Cem Meriç Şefikoğullari (Student Research Assistant)
  • Armin Ebrahimi Saba (Student Research Assistant)
  • Tim Leon Metz (Student Research Assistant)

Funding

  • BMFTR

Project Time

  • 01/2026 - 12/2027

Homepage

Description

As AI-native Radio Access Networks (RANs) emerge as a cornerstone of 6G and beyond next-generation wireless networks, ensuring the explainability and trustworthiness of AI-driven network management becomes a critical challenge. Unlike prior literature research that focuses on optimizing AI models for efficiency and accuracy, this project introduces a first-of-its-kind Explainable and Trustworthy AI (XAI) framework specifically designed for realtime, high-risk scenarios such as Ultra-Reliable Low-Latency Communications (URLLC) and next-generation URLLC (xURLLC).

Last modified: 2026-02-03