Abstract
Abstract
The advancement of 5G and the emerging vision of 6G are transforming mobile networks into intelligent and adaptive infrastructures, presenting significant opportunities alongside considerable technical and operational challenges. In 6G networks, ubiquitous integration of artificial intelligence (AI) is expected across all layers, enabling autonomous decision-making, proactive management, and unprecedented service personalization. This thesis explores how AI can address key challenges in three vital domains of mobile network operations. It investigates AI-driven approaches for predicting radio link failures to enable proactive interventions, minimizing disruptions and ensuring seamless connectivity even under adverse conditions. It further examines how AI can analyze and model human mobility patterns from network data, generating critical insights that support disaster response, urban planning, and public safety, particularly in the wake of large-scale emergencies. Lastly, it focuses on AI-based strategies to optimize energy consumption in mobile networks, developing intelligent methods to reduce power usage without compromising coverage or service quality. Collectively, these contributions underscore AI’s transformative role in shaping the future of mobile communications, positioning next-generation networks to meet escalating demands for performance, resilience, and sustainability, while contributing to societal welfare and environmental responsibility.