5 papers
Against the Monolithic Wireless World Model: Why NextG Needs Composable and Agentic Intelligence
Aladin Djuhera, Farhan Ahmed, Vlad C. Andrei +4
AI-native 6G visions increasingly invoke wireless foundation models, large multimodal models, and wireless world models as the natural endpoint of AI-native networking, drawing an…
MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction
Aladin Djuhera, Haris Gacanin, Holger Boche
Recent works have demonstrated that attention-based transformer and large language model (LLM) architectures can achieve strong channel state prediction (CSP) performance by captur…
AI-Programmable Wireless Connectivity: Challenges and Research Directions Toward Interactive and Immersive Industry
Haris Gacanin
This vision paper addresses the research challenges of integrating traditional signal processing with Artificial Intelligence (AI) to enable energy-efficient, programmable, and sca…
R-MTLLMF: Resilient Multi-Task Large Language Model Fusion at the Wireless Edge
Aladin Djuhera, Vlad C. Andrei, Mohsen Pourghasemian +3
Multi-task large language models (MTLLMs) are important for many applications at the wireless edge, where users demand specialized models to handle multiple tasks efficiently. Howe…
Robust Communication and Computation using Deep Learning via Joint Uncertainty Injection
Robert-Jeron Reifert, Hayssam Dahrouj, Alaa Alameer Ahmad +2
The convergence of communication and computation, along with the integration of machine learning and artificial intelligence, stand as key empowering pillars for the sixth-generati…