6 citations · 7 across the 11 of their papers we have counts for
4 papers · 1 filter
From Intents to Actions: Agentic AI in Autonomous Networks
Burak Demirel, Pablo Soldati, Yu Wang
Telecommunication networks are increasingly expected to operate autonomously while supporting heterogeneous services with diverse and often conflicting intents -- that is, performa…
Practical Policy Distillation for Reinforcement Learning in Radio Access Networks
Sara Khosravi, Burak Demirel, Linghui Zhou +2
Adopting artificial intelligence (AI) in radio access networks (RANs) presents several challenges, including limited availability of link-level measurements (e.g., CQI reports), st…
Generalization in Reinforcement Learning for Radio Access Networks
Burak Demirel, Yu Wang, Cristian Tatino +1
Modern RAN operate in highly dynamic and heterogeneous environments, where hand-tuned, rule-based RRM algorithms often underperform. While RL can surpass such heuristics in constra…
Design Principles for Model Generalization and Scalable AI Integration in Radio Access Networks
Pablo Soldati, Euhanna Ghadimi, Burak Demirel +3
Artificial intelligence (AI) has emerged as a powerful tool for addressing complex and dynamic tasks in radio communication systems. Research in this area, however, focused on AI s…