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An Extensible Framework for AI-Native Cellular Networks

YESDR (pronounced “Yes Dee Are”) is a modular standard-oriented framework for end-to-end cellular wireless experimentation from PHY to Core Network using Software-Defined Radios (SDRs).

Designed for flexibility, teaching, and research, YESDR enables AI-driven wireless innovation, including channel prediction, spectrum sensing, protocol optimization, dynamic spectrum access, traffic forecasting, and network automation. It provides a lightweight alternative to full 3GPP stacks, ideal for rapid prototyping and experimentation.

Who It’s For

  • Researchers and students in wireless, SDR, AI, 5G/6G
  • University labs, engineering colleges, and educators
  • Deep-tech startups and teams building 5G/6G testbeds
  • Developers exploring new RAN/Core protocols, MEC, ORAN

Key Features

  • Research-Oriented Standard Framework: An academic-friendly alternative to full 3GPP stacks for learning, teaching, and research.

  • Full‑Stack Customization: Complete control across Core Network and RAN protocols, spanning GTP and control signaling down to PDCP → RLC → MAC → PHY, enabling deep end-to-end protocol experimentation and innovation.

  • Python/C++ Dual Availability: Python for rapid research and prototyping, with a clear path to high-performance C++ deployment.

  • Hardware-Independent: Unified SDR abstraction enabling operation across multiple SDR platforms.

  • Community‑Driven Framework: Open, extensible, and designed for collaborative development.

  • Interoperability Ready: Designed to integrate with OpenAirInterface, Free5GC, Open5GS, UERANSIM, and potential ORAN‑based components for with real‑world 5G/6G experimentation.