6 papers
MAC-Gyver: Open, Programmable, Scheduling for AI-RAN 6G Systems
Maxime Elkael, Reshma Prasad, Tamerlan Aghayev +3
Cellular networks are integrating Artificial Intelli- gence (AI) into radio access network control. The MAC scheduler is a promising target because it allocates a limited resource,…
GENESIS: Harnessing AI Agents for Autonomous 6G RAN Synthesis, Research, and Testing
Tamerlan Aghayev, Maxime Elkael, Michele Polese +11
Cellular research and development (R&D) is throttled by six structural processes that each consume months of manual engineering work per iteration: (i) synthesizing new features fr…
BLINC: Context-Specific Causal Learning for Automated RAN Configuration
Reshma Prasad, Michele Polese, Tommaso Melodia
Radio Access Network (RAN) configuration has traditionally required significant manual effort due to indirect causal dependencies between observable Key Performance Indicators (KPI…
Joint Routing, Resource Allocation, and Energy Optimization for Integrated Access and Backhaul with Open RAN
Reshma Prasad, Maxime Elkael, Gabriele Gemmi +6
As networks evolve towards 6G, Mobile Network Operators (MNOs) must accommodate diverse requirements and at the same time manage rising energy consumption. Integrated Access and Ba…
RANalyzer: Automated Continuous RAN Software Evaluation and Regression Analysis
Ravis Shirkhani, Reshma Prasad, Leonardo Bonati +2
Software-driven O-RAN architectures enable rapid innovation through frequent, independent updates to virtualized components. However, attributing performance variations to specific…
ALLSTaR: Automated LLM-Driven Scheduler Generation and Testing for Intent-Based RAN
Maxime Elkael, Michele Polese, Reshma Prasad +2
The evolution toward open, programmable O-RAN and AI-RAN 6G networks creates unprecedented opportunities for Intent-Based Networking (IBN) to dynamically optimize RAN[...]. However…