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NSFDirectorate for Computer and Information Science and Engineering

Planning: AI Ready; Accelerating Innovation in Distributed AI Applications using an Open Radio Access Network (O-RAN) Testbed

Active
Institution
Virginia Polytechnic Institute and State University, VA
Principal investigator
Naren Ramakrishnan
Funding
$200K
Duration
2025–2027
Open portfolio

Moonbase score

Still being scored

Abstract

This project will plan for a wireless network testbed with integrated Artificial Intelligence (AI) capabilities to enable developing and testing AI-driven solutions for emerging industries critical to national prosperity, including agriculture, transportation, unmanned aerial systems, and smart cities. The testbed will enable modeling and design of a range of applications such as AI-powered drones for delivering supplies to citizens, improving spotty coverage in locations like farms, enhancing transportation safety, and securing supply chains. The project will also provide hands-on interdisciplinary training to prepare a talented workforce for careers at the intersection of AI and wireless technologies. Through open access, collaborative workshops, and robust governance, the testbed will support the transition to next-generation AI-enabled wireless systems. The proposed testbed will facilitate development of specialized AI foundation models trained on domain-specific knowledge, benchmark datasets, communication protocol settings, and user activity. These models will leverage real-time wireless data to optimize network configurations, resource allocation, and autonomous agent behaviors. The testbed infrastructure will feature a large-scale indoor radio grid and an outdoor corridor spanning farm, urban, and drone environments, all accessible remotely via secure cloud-native platforms. The planning project will organize scenario-based workshops with academic and industry stakeholders to define use cases, access policies, and governance structures, ensuring long-term sustainability and responsiveness to community needs. Expected outcomes include a scalable, AI-Ready testbed supporting end-to-end experimentation, new methods for adaptive and resilient wireless networks, and a foundation for future innovations in distributed AI applications and next-generation wireless research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Naren RamakrishnanPI
  • Lingjia LiuCo-PI
  • Eric W BurgerCo-PI
  • Brian MayerCo-PI
  • Aloizio Da SilvaCo-PI

LOADING MOONBASE SCORE

Directorate for Computer and Information Science and EngineeringTIP-CHIPS KTA-1 AI-MLwirelesstestbedradiotransportationgovernancedistributedsmart citiesnext-generation

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