Generalized & Explainable 6G Mobile Intelligence

Purpose and Goal

This project focuses on developing generalized and explainable mobile intelligence for future 6G networks. The project aims to support near-real-time mobile intelligence for diverse teleoperation use cases and to investigate how AI-driven mobile intelligence can be deployed across 6G network layers while co-existing with conventional communication methods.

The overall goal is to develop a hybrid and trustworthy approachintegrating AI with conventional methods across the 6G protocol stack, emphasizing generalization, explainability, and low-latency operation in dynamic and heterogeneous environments.

Research Gaps

The project addresses critical research gaps in low-latency and trustworthy mobile network intelligence, including wireless channel variability, efficient data handling, and AI/data quality. Key challenges include the complexity of AI integration, interoperability among components, and meeting strict latency and computational constraints at the network edge.

Additional challenges arise in deployment and maintenance, including skill shortages, deployment and operational costs, and regulatory compliance requirements related to fairness, transparency, and standardization. Fragmentation across standardization bodies such as 3GPP and the O-RAN Alliance adds further uncertainty. A central challenge remains balancing AI model generalizability and explainability with performance and efficiency.

Mitigation

The project addresses these challenges through a combination of theoretical and experimental research, ensuring that solutions align with the principles of generalized and explainable AI across the B5G and edge–cloud continuum. By bridging research gaps and translating theory into practice, project supports the development of transparent, trustworthy, and generalizable mobile intelligence frameworks for future 6G systems.

Impact

By validating its methods through a 6G teleoperation use case, project will contribute foundational knowledge toward trustworthy and explainable remote operation, industrial automation, and other mission-critical digital services. The project supports future digital infrastructure where generalized and explainable AI enables communication systems to operate effectively in dynamic and heterogeneous environments.