AI-RAN: The Future of Wireless Networks
The Rise of AI-RAN
AI is transforming industries, enterprises, and consumer experiences in new ways. Generative AI models are moving towards reasoning, agentic AI is enabling new outcome-oriented workflows, and physical AI is enabling endpoints like cameras, robots, drones, and cars to make decisions and interact in real-time. The common glue between all these use cases is the need for pervasive, reliable, secure, and super-fast connectivity.
The Need for AI-RAN
Telecommunication networks must prepare for this new kind of AI traffic, which can come directly through the fronthaul wireless access network or backhauled from the public or private cloud as a completely standalone AI inferencing traffic generated by enterprise applications. Local wireless infrastructure offers an ideal place to process AI inferencing. This is where a new approach to telco networks, AI radio access network (AI-RAN), stands out.
The AI-RAN Solution
SoftBank and NVIDIA have fast-tracked AI-RAN commercialization with its successful outdoor field trial in Fujisawa City, Kanagawa, Japan. This achievement marks multiple steps forward for AI-RAN commercialization and provides real proof points addressing industry requirements on technology feasibility, performance, and monetization.
The AI-RAN Solution Components
The SoftBank AI-RAN solution combines hardware and software components from NVIDIA and ecosystem partners, hardened to meet carrier-grade requirements. The solution enables a full 5G vRAN stack that is 100% software-defined, running on NVIDIA GH200 (CPU+GPU), NVIDIA Bluefield-3 (NIC/DPU), and Spectrum-X for fronthaul and backhaul networking. It integrates with 20 radio units and a 5G core network, connecting 100 mobile UEs.
AI-RAN Multi-Tenancy and Orchestration
One of the first principles of AI-RAN technology is to be able to run RAN and AI workloads concurrently and without compromising carrier-grade performance. This multi-tenancy can be either in time or space: dividing resources based on time of day or based on percentage of compute. This also implies the need for an orchestrator that can provision, de-provision, or shift workloads seamlessly based on available capacity.
AI-RAN Marketplace
With a new capacity for AI computing now available on distributed AI-RAN infrastructure, the question arises of how to bring AI demand to this AI computing supply. SoftBank used a serverless API powered by NVIDIA AI Enterprise to deploy and manage AI workloads on AI-RAN, with security, scale, and reliability.
AI-RAN Applications
In this outdoor trial, new edge AI applications developed by SoftBank were demonstrated over the live AI-RAN network, including a self-driving car and a robot struggling to keep up.
Energy Efficiency and Economics of AI-RAN
While the AI-RAN vision has been embraced by the industry, the energy efficiency and economics of GPU-enabled infrastructure remain key requirements, particularly how they compare to traditional CPU– and ASIC-based RAN systems. With this live field trial of AI-RAN, SoftBank and NVIDIA have not only proven that GPU-enabled RAN systems are feasible and high-performing but also significantly better in energy efficiency and economic profitability.
Accelerating AI-RAN with Aerial RAN Computer-1
NVIDIA recently announced the Aerial RAN Computer-1 based on the next-generation NVIDIA Grace Blackwell superchips as the recommended AI-RAN deployment platform. The goal is to migrate SoftBank 5G vRAN software from NVIDIA GH200 to NVIDIA Aerial RAN Computer-1 based on GB200-NVL2, which is an easier shift given the code is already CUDA-ready.
Conclusion
The validation of AI revenue upside, energy efficiency, and profitability of AI-RAN leaves no doubts about the feasibility, performance, and economic benefits of the technology. Going forward, exponential gains with each generation of NVIDIA superchips will multiply these benefits by orders of magnitude, enabling the much-awaited business transformation of telco networks.
Looking Ahead
SoftBank and NVIDIA are continuing to collaborate toward the commercialization of AI-RAN and bringing new applications to life. The next phase of the engagements will entail work on AI-for-RAN to improve spectral efficiency and on NVIDIA Aerial Omniverse digital twins to simulate accurate physical networks in the digital world for fine-tuning and testing.
FAQs
Q: What is AI-RAN?
A: AI-RAN (Artificial Intelligence Radio Access Network) is a new approach to telco networks that combines radio access network (RAN) and artificial intelligence (AI) to transform wireless networks.
Q: What are the benefits of AI-RAN?
A: AI-RAN offers improved spectral efficiency, reduced energy consumption, and increased profitability for telcos.
Q: What is the potential revenue upside of AI-RAN?
A: The potential revenue upside of AI-RAN is estimated to be 5x the cost of CapEx investment.
Q: What is the future of AI-RAN?
A: The future of AI-RAN is to transform telco networks and become an AI service provider, generating new revenue streams and opportunities.
Q: What is the role of NVIDIA in AI-RAN?
A: NVIDIA is a key partner in the development of AI-RAN, providing the necessary technology and expertise to enable the transformation of telco networks.
