From EdgeRIC to Intelligent RAN¶
EdgeRIC is a platform for Real-Time AI-in-the-Loop decision making and control in cellular networks.
Our goal is to build an intelligent RAN stack capable of real-time decision making by integrating:
Next-generation Fine-Grained Telemetry for deep network observability
Reasoning over Network Dynamics for adaptive control
Experience-Aware Learning for continuous improvement of network performance
Our Projects¶
Team¶
Team
Demos¶
Demos
BeamArmor
Anti-jamming: Controlling MIMO weights in realtime to steer the beam null toward the jammer
EdgeRIC: AI Scheduling
RL-based scheduling policy trained to maximize overall system throughput
SPARC: Multi-site Management
Interference-aware resource distribution across sites with Near-RT RIC
Events¶
EdgeRIC Events
Open Source Repositories¶
Open Source Repositories
5G Testbed¶
5G Testbed
EdgeRIC Core Architecture¶
EdgeRIC Architecture
Publications & Tutorials¶
Publications & Tutorials
EdgeRIC
Empowering Real-time Intelligent Optimization and Control in NextG Cellular Networks.
Beamarmor
Seamless anti-jamming in 5g cellular networks with mimo null-steering.
Tiny-Twin
A CPU-Native Full-stack Digital Twin for NextG Cellular Networks.
Windex
Realtime Neural Whittle Indexing for Scalable Service Guarantees in NextG Cellular Networks.
SPARC
Spatio-Temporal Adaptive Resource Control for Multi-site Spectrum Management in NextG Cellular Networks.
Datasets¶
Datasets
Funding¶
This work was funded primarily by NSF Grants CNS 2312978, CNS 2312979 and in part by CNS 1955696, ECCS 2030245, ARO grant W911NF- 19-1-0367.