NSF VINES Research ProjectOpen & Integrated Networks Edge Computing Non-Terrestrial Networks
An NSF VINES Collaborative Research Project

O2-RAN

Orbital Open Radio Access Network

AI-Native Open RAN for Non-Terrestrial Networks & Space-Based Edge Computing

Advancing open, intelligent and resilient connectivity across satellite, aerial and terrestrial networks through joint communication, computation and energy-aware orchestration.

Explore the Research View Demo Roadmap
O²-RAN conceptual architecture across space, air and ground: GEO and LEO satellites, inter-satellite links, HAPS and UAV swarms, ground terminals, direct-to-cell and IoT connectivity, alongside distributed O-RAN control including xApps, rApps, SMO, RIC, CU-DU, RU and AI/ML frameworks.
Figure 1. O²-RAN integrated space–air–ground network and intelligent O-RAN control architecture.View full size
THE PROJECT

Intelligent connectivity beyond terrestrial networks

Open, predictive, compute-aware communication across space, air and ground.

About O²-RAN

O²-RAN is a collaborative NSF VINES research project developing L/S-band radio and satellite payload technology alongside AI-native, compute-aware Open RAN architectures for non-terrestrial networks. The research responds to challenges caused by orbital motion, high Doppler shifts, variable backhaul and constrained onboard computing resources.

Its vision is an adaptable and interoperable architecture that coordinates communication, computation and energy across satellites, UAVs and terrestrial infrastructure.

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RESEARCH PROGRAM

Three research thrusts

Coordinated development of NTN-ready O²-RAN software, satellite and aerial hardware, intelligent orchestration, and integrated system validation.

THRUST 01

System Architecture & O-RAN for NTN

Design L/S-band satellite radio payloads and fronthaul, predictive/cooperative beamforming and NTN-aware RU/DU/CU and RIC control for orbital mobility.

THRUST 02

Communication-Aware Distributed Edge Intelligence

Develop compute-aware service models, Near-RT xApps and Non-RT rApps for predictive slicing, workload placement and edge offloading.

THRUST 03

End-to-End Use Case Integration

Integrate the full NTN O-RAN stack across mission-driven scenarios, validate KPIs and demonstrate interoperability across heterogeneous nodes.

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RESEARCH CAPABILITIES

Core Technical Directions

From a working O²-RAN software stack and satellite radio hardware to AI-native control and distributed edge computing.

01O²-RAN Architecture02O²-RAN Software Stack03L/S-Band Radio & RF04CubeSat Payload Integration05Predictive Beamforming06AI-Native RIC & Edge AI
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VALIDATION SCENARIOS

Research use cases

Project requirements and demonstrations are grounded in three representative applications.

UC 01

Disaster-Resilient Aerial Base Stations

UAV-mounted base stations restore communications in areas affected by damaged or unavailable ground infrastructure.

  • Rapidly deployable aerial connectivity
  • Resilient backhaul and adaptive network control
  • Service prioritization for emergency operations
UC 02

Direct-to-Cell Satellite & CubeSat Connectivity

CubeSat-class L/S-band radio payloads and regenerative NTN functions support a planned direct-to-cell validation pathway, building toward satellite links with user devices.

  • CubeSat direct-to-cell payload and testbed
  • Predictive beam, Doppler and handover management
  • NTN-aware RU/DU/CU integration
UC 03

UAV Swarms with MEC Offloading

Coordinated UAVs distribute sensing and AI workloads across aerial, satellite and ground edge resources.

  • Collaborative sensing and inference
  • Compute-communication co-optimization
  • Predictive workload migration
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DEMONSTRATION ROADMAP

Six planned milestones

A phased path from architecture validation to integrated space–air–ground demonstration.

Project-relative months (M6–M36). Locations, configurations and schedules are planned and subject to coordination.
M6Architecture
M11Emulation
M18Closed Loop
M23HIL
M30UAV Field
M36Integrated NTN
Early validation

Architecture, NTN emulation and RIC control (M6–M18)

System integration

Hardware-in-the-loop, UAV field trials and at-scale NTN integration (M23–M36)

Full demonstration schedule
RESEARCH CONSORTIUM

Team & Partners

Interdisciplinary collaboration with academic and industry researchers.

Farshad Firouzi
PROJECT LEADERSHIP

Farshad Firouzi

Project Lead & Principal Investigator

Johns Hopkins University

Meet the full team

Academic & industry collaboration

Arizona State UniversityClemson UniversityJohns Hopkins UniversityUCLAUniversity of MichiganGeneral AtomicsAetheroSkylark WirelessDASH Tech IC
PROJECT OUTPUTS

Publications & Resources

Peer-reviewed research, open-source tools and datasets will be posted when available.

Publications

Peer-reviewed papers, technical reports, presentations and research posters.

Content forthcoming

Software & Tools

O-RAN/NTN extensions, example configurations and publicly available research code.

Content forthcoming

Datasets & Demos

Validation datasets, experiment descriptions, benchmark materials and demonstration media.

Content forthcoming
Research resources
CONNECT WITH THE CONSORTIUM

Research collaboration & inquiries

For project information and research collaboration opportunities, visit the contact page.

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