4 papers
Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
Farhad Rezazadeh, Hatim Chergui, Merouane Debbah +2
In sixth-generation (6G) Open Radio Access Networks (O-RAN), proactive control is preferable. A key open challenge is delivering control-grade predictions within Near-Real-Time (Ne…
LiQSS: Post-Transformer Linear Quantum-Inspired State-Space Tensor Networks for Real-Time 6G
Farhad Rezazadeh, Hatim Chergui, Amir Ashtari Gargari +4
Proactive and agentic control in Sixth-Generation (6G) Open Radio Access Networks (O-RAN) requires control-grade prediction under stringent Near-Real-Time (Near-RT) latency and com…
Agentic World Modeling for 6G: Near-Real-Time Generative State-Space Reasoning
Farhad Rezazadeh, Amir Ashtari Gargari, Hatim Chergui +4
We argue that sixth-generation (6G) intelligence is not fluent token prediction but the capacity to imagine and choose -- to simulate future scenarios, weigh trade-offs, and act wi…
Toward Generative 6G Simulation: An Experimental Multi-Agent LLM and ns-3 Integration
Farhad Rezazadeh, Amir Ashtari Gargari, Sandra Lagen +3
The move toward open Sixth-Generation (6G) networks necessitates a novel approach to full-stack simulation environments for evaluating complex technology developments before protot…