Enhancing Reliability in 6G Networks Based on User-Driven AI

In the sixth-generation (6G) era of mobile networks, services will be focused on users, highlighting the need to pursue and adopt a user-centric approach. Artificial Intelligence and Machine Learning (AI/ML) integration into the 6G network is of paramount importance in this approach. Moreover, 6G mission-critical applications, such as remote surgery, metaverse, and autonomous vehicles, expect high Quality of Experience (QoE), which can only be ensured through strong network and service reliability. In this paper, we propose a novel AI-based framework for ensuring user-centric reliability on 6G networks that extends over the whole 6G edge-cloud continuum infrastructure. More specifically, we present two profiling methods (service and security) that identify and act proactively against malicious activities and infrastructure-related issues, taking into account the unique characteristics of each user. We also perform a correlation analysis aiming to designate the need to exploit these user-centric characteristics, e.g., user position, speed, etc., when optimizing the QoE and ensuring reliability.