Developer Zone#

Developer Extensions#

RIC Platform by Northeastern University#

The Northeastern University (NEU) Wireless Institute of Things (WIoT) Institute is advancing the integration of O-RAN technology with NVIDIA’s ARC-OTA platform. One research topic is integrating an end-to-end (E2E) O-RAN E2 interface within the ARC-OTA software stack. The integration leverages key components of the O-RAN ecosystem, including the O-RAN Software Community (OSC) RAN Intelligent Controller (RIC), and the OpenRAN Gym framework.

The integration enables two critical functionalities:

  • Streaming of key performance metrics (KPMs): The system can now transmit relevant performance data in real-time

  • Enforcement of control actions: Decisions made by the xApps on the near-real time (Near-RT) RIC can be implemented swiftly.

Recent Developments

In July 2023, NEU showcased a significant milestone:

  • A data-collection xApp running on an OSC RIC

  • Deployed in a fully automated OpenShift cluster

  • Connected to an InfluxDB database for telemetry storage

  • Visualization of on a Grafana dashboard.

Ongoing Work

NEU is currently focused on enhancing the system’s capabilities:

  • Near-RT Control: The team is working to enable Near-RT control functionalities on the existing infrastructure

  • 8-Node Deployment: The institute is supporting an 8-node NVIDIA ARC-OTA deployment, which serves as the testbed for these advancements.

This project represents a significant step forward in the implementation of O-RAN technology, potentially improving the flexibility, efficiency, and intelligence of radio access networks.

../../_images/neu-kpm-dashboard.png

Kubernetes Service Management by Sterling SkyWave#

Sterling SkyWave Service Management is a developer extension for NVIDIA ARC-OTA that enhances its capabilities with two key features:

  • Kubernetes (K8s) Service Orchestration: Utilizes Helm for application management and includes two main Helm charts: skywave-service-management for gNB servers and oai-5g-basic for CN5G servers. The extension supports both single-node and multi-node deployment topologies, offering flexibility in network setup.

  • Service Monitoring: Leverages open-source tools such as Grafana, Loki, Promtail, and Prometheus to provide comprehensive monitoring and visualization capabilities. It offers three default dashboards: ARC-OTA for gNB and UE status, GPU for NVIDIA Data Center GPU Manager (DCGM) metrics, and Host for system-level metrics.

The Sterling SkyWave Service Management extension is documented here.

Open5Gs by Northeastern University#

Northeastern University has successfully integrated and validated Open5Gs, an advanced 5G open-source core network, in their experimental lab setup using an OpenShift cluster. This achievement represents a significant step forward in 5G network R&D.

Key Achievements

  • Microservice Architecture: The core network is built on a microservice architecture, offering flexible deployment and scaling of individual network functions

  • Optimized User Plane Function (UPF): Delivers high-performance packet processing capabilities

  • User-Friendly SIM Management: Offers easier management of user SIMs through a graphical interface

  • Network Slicing Support: Enables the creating of multiple virtual networks on a single physical infrastructure

  • Deployment Flexibility: Open5Gs demonstrates remarkable versatility in deployment options:

    • Bare metal installation using standard Linux package managers

    • Containerized deployment using Docker

    • Virtualized approach utilizing Helm Charts on K8s and OpenShift

  • Performance and Compatibility: When integrated with NVIDIA’s ARC-OTA platform, Open5Gs exhibited impressive performance:

    • High Stability: Maintained consistent operation during testing

    • Sustained Performance: Met the performance expectations set for the ARC-OTA release

    • MIMO Compatibility: Successfully tested with OAI and 2-layer MIMO configurations

  • Implications for O-RAN Ecosystem: This successful integration underscores the potential of the disaggregated O-RAN ecosystem. It demonstrates that components from different vendors can seamlessly integrate, fostering innovation and flexibility in 5G network deployments.

The Open5Gs implementation at Northeastern University showcases the power of open-source solutions in advancing 5G technology. By leveraging microservices architecture and supporting various deployment methods, Open5Gs provides researchers and developers with a robust platform for exploring next-generation mobile network capabilities.

n48 (CBRS) O-RU Interoperability by Rice University#

The Rice University, Department of Electrical and Computer Engineering has made significant progress in enabling interoperability between NVIDIA ARC-OTA software with the Foxconn Citizens Broadband Radio Service (CBRS) O-RU (RPQN-4800E). This collaboration has yielded impressive results in lab testing, demonstrating the potential for advanced 5G and 6G research in the United States.

Key Achievements

  • Successful Testing: The team achieved stable connectivity for over an hour in an indoor lab environment

  • Operational Spectrum: Tests were conducted in a 100 MHz band (3.6-3.7 GHz)

  • Throughput Performance: Achieved 250 Mbps DL and 50 Mbps UL speeds

  • Equipment Used: Quectel RG520N UE module and OnePlus Nord 5G commercial handset

CBRS Spectrum Importance

The CBRS band (3.55-3.7 GHz) plays a crucial role in 5G deployment in the United States. The Federal Communications Commission (FCC) has opened this spectrum for shared access, implementing a three-tiered system:

  • Incumbent Users: Government bodies

  • Priority Access License (PAL): Acquired through FCC auctions or secondary market sublicensing

  • General Authorized Access (GAA): Available when incumbent and PAL users are inactive

This shared access model, particularly the GAA tier, makes the CBRS band ideal for 5G research and development (R&D). It offers opportunities for experimentation without the high costs associated with PAL access.

GPU MIG Partition by Sterling SkyWave#

The Sterling SkyWave GPU multi-instance GPU (MIG) Partition plugin is documented here.

Application Note

While running Aerial on a GPU partition device, the mps_sm_* parameters in the cuphycontroller config YAML file need to be adjusted accordingly such that the mps_sm_* value is not over the available streaming multiprocessors (SMs) of the selected MIG devices.

Please refer to the mps_sm_* configurations in cuphycontroller_P5G_FXN.yaml for the following cases:

  • Running Aerial with MIG disabled

    mps_sm_pusch: 108

mps_sm_pucch: 16

mps_sm_prach: 16

mps_sm_pdsch: 82

mps_sm_pdcch: 28

mps_sm_pbch: 18

mps_sm_srs: 16

  • Running Aerial with MIG enabled on mig-4g.48gb

    mps_sm_pusch: 42

mps_sm_pucch: 16

mps_sm_prach: 16

mps_sm_pdsch: 58

mps_sm_pdcch: 10

mps_sm_pbch: 8

mps_sm_srs: 8

  • Running Aerial with MIG enabled on mig-3g.48gb

    mps_sm_pusch: 40

mps_sm_pucch: 16

mps_sm_prach: 16

mps_sm_pdsch: 52

mps_sm_pdcch: 10

mps_sm_pbch: 8

mps_sm_srs:  8

Developer Use Cases#

We love to see how ARC-OTA is being used by developers, researchers, and the industry. Send an email to aerial-info@nvidia.com with your project description and links to the project and code repository (e.g. GitHub).

The following are example developer use cases.

ETH Zurich#

Integrated Information Processing Group

The Integrated Information Processing (IIP) Group at ETH Zurich has successfully deployed a 5G vRAN system based on the NVIDIA ARC-OTA platform. This system is fully software-defined and standards-compliant, enabling rapid prototyping and verification of novel baseband algorithms under real-world conditions.

Key Features and Advantages

  • Software-Defined System: Allows implementation of novel baseband algorithms in CUDA for real-time execution and evaluation through OTA experiments.

  • Flexibility: Offers the capability to extract real-time data from various parts of the signal processing chain, which is crucial for ML-assisted baseband algorithms.

    • The following UEs have been successfully tested in the system: iPhone 14 Pro, iPhone 15 Pro, iPhone 16E, Samsung Galaxy S23, Google Pixel 7, OnePlus Nord, Quectel RMU500EK

  • Cost-Effective: Reduces development time and verification costs compared to hardware-based prototypes using FPGAs or ASICs.

Research Goals

  • Develop novel ML-assisted baseband algorithms for future 5G and 6G wireless systems

  • Optimize and validate solutions through OTA experiments on a real-world system

  • Continue work on user positioning methods using self-supervised channel charting with channel state information (CSI)

ML-Assisted Iterative MIMO Detection and Decoding

The group aims to implement their Deep-Unfolded Interleaved Detection and Decoding (DUIDD) receiver architecture on the NVIDIA platform. This approach:

  • Fuses MIMO data detection and channel decoding with ML techniques

  • Has shown 1.4 dB performance gains in simulations over classical iterative detection and decoding solutions

  • Will be evaluated under realistic conditions to assess its efficacy and potential for adaptation to instantaneous system and channel conditions

This real-world 5G system provides a powerful platform for advancing wireless communications research beyond simulations, enabling the development and validation of innovative algorithms in realistic operational environments.

Real-World 5G System Blog

NVIDIA's ARC-OTA platform enables us to develop novel machine-learning-assisted baseband algorithms for 6G. - Christoph Studer, Professor at ETH Zurich Research focus: ML-Assisted MIMO detection, decoding, and user positioning

HHI Fraunhofer#

6G-RIC Is Significantly Advancing Its Open Test Environment

Open source, E2E deployments are key, offering 6G-RIC researchers and associated startups a highly accessible and versatile platform for experimentation. This encourages innovation and facilitates the testing of emerging technologies, protocols, and applications. The integration of an Open RAN network, based on open-source technologies and NVIDIA ARC-OTA, marks a significant milestone for our project. The GPU-centric design is ideal for integrating AI/ML and expediting the creation of demonstrators, which once required significant development time.

../../_images/20240229_ARC_blog_post_HHI_EO_review-1.jpg

Northeastern University#

Northeastern University’s Institute for the Wireless Internet of Things (WIoT) and its Open6G R&D Center have launched the first production-ready private 5G network fully automated through AI. This groundbreaking system is built on NVIDIA ARC-OTA platform, enabling a fully virtualized, programmable O-RAN compliant network in a campus environment.

Key features of this innovative network include:

  • Connectivity for 5G devices, supporting video conferencing, browsing, and streaming for experiential learning activities

  • Built on open-source programmable components, utilizing compute solutions from partners like Dell Technologies and NVIDIA

  • Employs zTouch, Northeastern’s AI-based management, control, and orchestration framework for streamlined deployment and automated configuration

  • Runs on Dell servers using OAI and Open5Gs for RAN and core network implementations

  • Features base stations based on the NVIDIA ARC-OTA, integrating a GPU-based PHY layer.

  • The following UEs have been successfully tested in the system: OnePlus AC2003 Nord Samsung Galaxy S23, Sierra Wireless EM9191 NR 5G Modem, OAI Soft-UE.

The network showcases key features of next-generation wireless systems:

  • Openness and programmability following the O-RAN architecture

  • Resiliency and self-healing behavior through the zTouch automation framework

  • Intelligent orchestration for managing xApps, rApps, and dApps.

  • 55 UEs have been tested in a RF cabled test with the Keysight eLSU.

Currently deployed at Northeastern University’s Boston campus, with plans to extend to the Burlington campus, this private 5G network offers unique opportunities for research in next-generation wireless technologies, including spectrum sharing mechanisms, AR/VR, E2E slicing solutions, and advanced security solutions.

There are more details for this project in this blog post. Visit https://wiot.northeastern.edu/ for information about the Northeastern Institute for the WIoT program.

../../_images/ea_northeastern1.png ../../_images/ea_northeastern2.png

OpenAirInterface Software Alliance#

The OpenAirInterface (OAI) Alliance has demonstrated a 5G vRAN using NVIDIA Aerial CUDA-Accelerated RAN (formerly known as Aerial SDK) at the O-RAN virtual exhibition 2023. This demonstration showcases the integration of NVIDIA’s L1 with OAI’s L2+ to create an accelerated 5G vRAN.

Key Features of the Demonstrations

  • Hardware Setup: The gNB (O-CU and O-DU) runs on a Dell server with an NVIDIA A100 Tensor Core GPU and ConnectX-6 DX SmartNIC

  • Network Configuration: Uses O-RAN 7.2x fronthaul split, connecting to a commercial O-RU and a 5G phone

  • Containerized Environment: Two containers run on the edge server - one for NVIDIA Aerial L1 and another for OAI L2+

  • Core Network: Runs on a separate server with virtualized network functions (AMF, SMF, UPF) in different containers.

Technical Specifications

  • Supports frequency range one, 30 kHz subcarrier spacing, 100 MHz bandwidth

  • TDD config: 2.5ms periodicity, 3ms DL, 1ms UL

  • Supports 2 layers of DL, 1 UL, and 1 cell.

Significance

This demonstration represents a shift towards software-defined, C/C++ programmable 5G base stations, enabling rapid prototyping and improved feature development without FPGA programming. It simplifies the development and testing of new 5G technology and applications, offering a cost-effective and performant alternative to traditional purpose-built custom hardware.

Learn more about this collaboration at the links below:

Rice University#

Rice University outlines how NVIDIA ARC-OTA platform makes several key contributions to the research described in this blog post:

  • ARC-OTA provides a 5G-compliant software-defined system that enables dataset generation at each layer of the network, which is crucial for training AI models

  • The platform offers capabilities that help researchers pursue:

    • Representative datasets

    • E2E OTA performance benchmarking

    • Real-time implementation and performance evaluation of new algorithms

  • For deep learning-based MIMO detection research, NVIDIA ARC-OTA allows for:

    • Collection of real-world 5G-compliant data

    • Real-time implementation of AI-based detection algorithms on NVIDIA GPUs

  • In radar detection and coexistence studies, the platform is used to:

    • Collect CSI from users affected by radar signals

    • Potentially implement real-time AI-based radar detection techniques

  • For self-adapting vRANs research:

    • It enables benchmarking of wireless performance under varying compute loads

    • Allows investigation of GPU resource allocation for achieving specific data rates

    • Supports the development of AI-based schedulers that jointly allocate compute and radio resources

NVIDIA RC-OTA platform serves as a crucial tool for researchers to generate real-world data, implement and evaluate AI algorithms in real-time, and explore various aspects of 5G and beyond network optimization.

Visit https://wireless.rice.edu/ for information about the Rice Wireless program.

|project_abbr| provides an exciting opportunity to demonstrate the power of Al in enhancing the performance and capabilities of 5G networks and beyond. -Ashutosh Sabharwal, Professor & Department Chair at Rice ECE. AI enhanced MIMO

Singapore University of Technology and Design (SUTD) and Keysight Technologies#

Under the umbrella of the AI-RAN Alliance, the Singapore University of Technology and Design (SUTD), in partnership with Keysight Technologies, used ARC-OTA and Aerial Data Lake to implement a real-time OTA system that adaptively partitions an AI/ML image classification inference model between user equipment and infrastructure compute resources. The model split point is a function of the propagation channel which itself is determined by real-time spectrum sensing. This work shows how critical metrics such as privacy, end-to-end latency, energy efficiency and throughput can be optimized as a function of channel.

More information, including a video of the demonstration, can be found here.

../../_images/sutd_diagram_1.png

DeepSig Develops Algorithms for Learned Air Interface for 6G#

This research work by AI-RAN alliance’s member company, DeepSig is focused on developing and benchmarking an AI-native air interface for 6G physical layer. The goal is also to experiment with pilot-free or pilot-in-the-loop operations, jointly learning the modulation functions in the base station and in the UE. The approach aims to optimize the radio resource utilization for improved capacity over a wide range of specific and broad channel conditions.

The hypothesis of this experiment is to challenge the current 5G air interface design that is model based with convenient assumptions on modulation, pilot, and frame design even though these are performance limiting. AI-native air interface allows AI to inherently design the waveform for a given site that will perform better. The approach allows AI to find the performance and capacity maxima by jointly learning and optimizing the waveform.

The setup uses the ARC-OTA as the basis with a programmable UE implemented on a Jetson AGX Orin device:

../../_images/deepsig_1.png

The leaned air interface shows significant promise of improved site-specific performance as demonstrated by DeepSig at MWC2025:

../../_images/deepsig_2.png

More information on this can be found here.

Selected Developer News and Publications#

Developer(s)/Author(s)

Title

O-RAN Spring 2024 Plugfest at Northeastern OTIC

Automating and Testing End-to-End O-RAN Systems

O-RAN Global Spring PlugFest 2024 at EURECOM

O-RAN Global Plugfest Spring 2024

Northeastern University

X5G: An Open, Programmable, Multi-vendor, End-to-end, Private 5G O-RAN Testbed with NVIDIA ARC and OpenAirInterface (Journal extension under review - focus RIC)

Sterling

Sterling introduces SkyWave

Anupa Kelkar

A brief description of ARC-OTA in two slides

NTIA, Office of Public Affairs

Northeastern and Rice university NTIA NOFO 1 win Biden-Harris Administration Award for Nearly $80M for Wireless Innovation

Eidgenössische Technische Hochschule Zürich

Real-World 5G System

Northeastern University

Northeastern University launches Fully Automated and Virtualized O-RAN Private 5G Network with AI Automation

TMCnet News

2023 Open Ran Product of the Year Award Winners

Davide Villa, Imran Khan, Florian Kaltenberger, Nicholas Hedberg, Ruben Soares da Silva, Anupa Kelkar, Chris Dick, Stefano Basagni, Josep M. Jornet, Tommaso Melodia, Michele Polese, Dimitrios Koutsonikolas

An Open, Programmable, Multi-vendor 5G O-RAN Testbed with NVIDIA ARC-OTA and OpenAirInterface

Anupa Kelkar, Chris Dick

Introducing NVIDIA Aerial Research Cloud for Innovations in 5G and 6G

Florian Kaltenberger, Irfan Ghauri, Chris Dick, Anupa Kelkar, Lopamudra Kundu

Demonstration of NVIDIA Aerial SDK and OAI 5G vRAN and CN Virtual Exhibition

OpenAirInterface

OpenAirInterface Demonstrates 5G Virtual RAN with NVIDIA Aerial SDK

Jeffrey Andrews

Site Specific Deep Learning for the 6G Air Interface

Rahman Doost-Mohammady, Santiago Segarra, Ashutosh Sabharwal

Rice University Blog

Chris Dick

IEEE Keynote: The NVIDIA Roadmap tp AI-Infused 6G
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