Case Study: KU Leuven University achieves AI-driven wireless reliability, energy efficiency and enhanced safety with HPE Aruba Networking

Elevating wireless connectivity to new heights with AI

KU Leuven researchers are tackling unreliable signal reception, imprecise indoor localization and the emerging challenges of the 5G-to-6G transition—issues that can affect everything from everyday connectivity to critical safety scenarios like locating a fallen person. Their work focuses on boosting network reliability, adaptability and energy efficiency while improving sensing and localization in complex indoor environments.

Using custom machine learning and deep neural networks—accelerated on HPE ProLiant DL380 Gen11 servers with NVIDIA A100 GPUs—the team dynamically tunes network parameters, mitigates analog front-end imperfections and detects anomalies. The result is faster, more stable and energy-efficient wireless networks with improved indoor positioning and safety, simplified network management and greater capacity for next‑generation deployments.

KU Leuven university

Franco Minucci

Post-Doctoral Researcher