Poster
in
Workshop: Machine Learning for Wireless Communication and Networks (ML4Wireless)
Position Paper: Rethinking AI/ML for Air Interface in Wireless Networks
Georgios Kontes · Diomidis Michalopoulos · Birendra Ghimire · Christopher Mutschler
AI/ML research has predominantly been driven by domains such as computer vision, natural language processing, and video analysis. In contrast, the application of AI/ML to wireless networks, particularly at the air interface, remains in its early stages. Although there are emerging efforts to explore this intersection, fully realizing the potential of AI/ML in wireless communications requires a deep interdisciplinary understanding of both fields. We provide an overview of AI/ML-related discussions in 3GPP standardization, highlighting key use cases, architectural considerations, and technical requirements. We outline open research challenges and opportunities where academic and industrial communities can contribute to shaping the future of AI-enabled wireless systems.