Artificial Intelligence Radio Access Network (AI-RAN) with Digital Twin

Artificial Intelligence Radio Access Network (AI-RAN) with Digital Twin

Executive Summary

This lab-scale mmWave AI-Based RAN testbed integrates OAIBox, NVIDIA Aerial RAN, NI USRP X410, TMYTEK mmWave beamformers, and a high-fidelity Digital Twin pipeline using Remcom Wireless InSite and ANSYS HFSS SBR+ to create a flexible, programmable, and AI-native 5G/6G research environment. It enables real-time prototyping of mmWave physical layers, AI-driven beam management, hybrid beamforming, AI-enhanced MAC scheduling, and joint communication–sensing (ISAC) experiments. The platform supports end-to-end 5G NR PHY/MAC stacks, GPU-accelerated baseband processing, and mmWave RF front-ends for high-bandwidth OTA testing, while the Digital Twin provides physics-accurate ray-tracing, EM-based antenna modeling, and virtual–to–real co-simulation for channel prediction, beam optimization, and AI dataset generation.

Core Components

OAIBox – OpenAirInterface RAN Framework

The testbed uses OAIBox as a compact and modular implementation of the full OAI RAN stack. It provides:

  • Support for 5G SA/NSA gNB and UE
  • Flexible PHY–MAC integration
  • Customizable scheduling, HARQ, and protocol features
  • Real-time experimentation with RAN procedures and RRC signaling

OAIBox acts as the protocol and control anchor of the testbed.

NVIDIA Aerial RAN (cuPHY + cuMAC)

The NVIDIA Aerial platform provides GPU-accelerated baseband processing and AI-native PHY/MAC capabilities:

  • cuPHY for NR physical-layer DSP on GPUs
  • cuMAC for dynamic MAC scheduling on GPU
  • TensorRT for real-time neural inference
  • Support for multi-cell, multi-user, and high-throughput pipelines

Aerial enables experiments in:

  • AI-driven beam selection and prediction
  • Neural channel estimation
  • Predictive link adaptation and blockage detection

NI USRP X410 – Wideband Software-Defined Radio

The USRP X410 serves as the flexible transceiver frontend with:

  • Up to 400 MHz instantaneous bandwidth
  • Four synchronized TX/RX channels
  • 10/1588 PTP synchronization
  • Digital IF for integration with NVIDIA Aerial

It supports:

  • mmWave IF/baseband experimentation
  • Real-time CSI acquisition
  • Multi-subarray MIMO and wideband waveform prototyping

TMYTEK mmWave Beamformers (BBox, UD-Box, Beamform Modules)

TMYTEK hardware provides programmable mmWave RF front-ends:

  • UD-Box for 24–32 GHz up/down-conversion
  • BBox One / BBox Lite beamforming arrays
  • API-driven phase/gain control
  • Rapid beam steering and codebook-based operation

These modules enable:

  • Hybrid or analog beamforming
  • Electronic steering up to ±60°
  • Multi-beam and multi-focus mmWave experimentation

Digital Twin

A full Digital Twin framework integrates high-fidelity electromagnetic simulation with the physical testbed. This enables reproducible channel modeling, data augmentation, and virtual-to-real RAN optimization.

Remcom Wireless InSite – Ray Tracing Propagation

Wireless InSite provides a large-scale propagation environment supporting:

  • GPU-accelerated 3D ray tracing
  • Detailed mmWave diffraction, reflection, and scattering
  • Urban, indoor, and open-field scenario modeling
  • Material-dependent loss and blockage effects
  • Beam-level channel prediction

ANSYS HFSS SBR+ – Full-Wave EM Modeling

HFSS SBR+ enables full-wave modeling of:

  • Antenna arrays, including TMYTEK beamformers
  • Reflectarrays, metasurfaces, and RIS
  • Realistic gain patterns for hybrid beamforming
  • Complex EM interactions under mmWave frequencies

Capabilities

AI-Enhanced RAN Intelligence

  • Neural beam prediction and tracking
  • AI-based MAC scheduling
  • CSI-driven link adaptation models
  • Blockage prediction and proactive beam switching

mmWave PHY/MAC Research

  • Hybrid and digital beamforming
  • Channel sounding and dataset generation
  • Evaluation of mobility, rotation, and blockage
  • 5G NR waveform prototyping

Flexible RAN Architecture

  • O-RAN 7.2 split between OAIBox and Aerial
  • Multi-RU and multi-sector emulation
  • Edge-cloud cooperative intelligence

ISAC (Integrated Sensing and Communication) Extensions

  • Joint radar–communication waveform experiments
  • 2D/3D angle estimation
  • Passive sensing with GPU-accelerated FFT pipelines

Digital Twin–Driven Insights

  • Predictive channel statistics and blockage maps
  • Virtual scenario pre-testing
  • Dataset augmentation for AI training
  • Virtual beam codebook optimization