Explainable and Trustworthy AI/ML for 6G

Institutions

  • TU Berlin
  • Fraunhofer HHI
  • Huawei

Team @ TKN

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: 2025-10-26