SoftBank and Ericsson achieve interworking between AITRAS Orchestrator and Ericsson IAP

Demonstrating AI-RAN innovation through the dynamic allocation of computing resources across AI and RAN workloads.

SoftBank Corp. (President & CEO: Junichi Miyakawa, “SoftBank”) announced that, as part of its ongoing joint research and development efforts with Ericsson (NASDAQ: ERIC), the two companies have newly defined and implemented a way for the orchestrator of SoftBank’s AI-RAN product under development, AITRAS (“AITRAS Orchestrator”), to integrate and coordinate with Ericsson Intelligent Automation Platform (“EIAP”), an O-RAN–compliant Service Management and Orchestration (“SMO¹”) platform responsible for RAN management and control, toward the integrated management and operation of AI (artificial intelligence) processing and RAN (Radio Access Network) control, including through rApps (non-real time RAN automation applications).

The setup enables coordination between rApps running in the RAN domain and AI workloads hosted on separate compute clusters, without co-locating the two on the same server. Through this framework, Ericsson and SoftBank are demonstrating how non-real time RAN control loops, end-user AI workloads, and automation can interact seamlessly, and dynamic allocation of computing resources across AI and RAN domains has become possible, while maintaining coordination between network and AI inference infrastructure.

The initiative has proven successful, with AI and RAN use cases successfully demonstrated.

Background and Challenges

AI-and-RAN is a concept within AI-RAN that aims to efficiently utilize server computing resources by running workloads with different characteristics—AI workloads and RAN workloads—on a single virtualized infrastructure.

As the use of AI expands and demand for communication networks continues to grow, there is an increasing need for management and operational technologies that can monitor demand for computing resources used for AI processing and RAN control in real time and dynamically and flexibly allocate those resources. In particular, interworking and role sharing between an orchestrator that manages and controls the overall AI-RAN platform and infrastructure, and SMO that manages and controls the RAN domain, often through the operation of rApps, represent key challenges in the implementation of AI-RAN.

Overview of the Initiative

Against this backdrop, SoftBank and Ericsson defined and method to enable interworking between the AITRAS Orchestrator and the Ericsson Intelligent Controller (EIC) and Ericsson Orchestrator Lifecycle Manager (EO-LM), which are components of EIAP, and built a system in which each element operates in coordination. The project also illustrates for the first time how EIAP may be used to coordinate and manage an IT, as well as its network environment.

In this initiative, when the EIAP requests the use of computing resources based on RAN requirements, driven, for example, by an rApp, the AITRAS Orchestrator allocates the required computing resources by taking into account overall utilization of the AI-RAN platform. This configuration enables computing resources that are temporarily required for RAN use to be dynamically allocated from the AI-RAN platform to the EIAP and promptly returned once processing is complete.

Specifically, the AITRAS Orchestrator identifies Kubernetes² clusters that can be allocated for RAN use and generates temporary access tokens, which are provided to the EIAP. The EIAP then utilizes the relevant clusters as extended resources of the O-Cloud³ and executes the rApp⁴ workloads. After the workloads complete execution, the EIAP returns the computing resources to the AITRAS Orchestrator.

Through this coordination between two functions responsible for managing different domains, dynamic adjustment and allocation of computing resources required for both RAN and AI use cases has been achieved.

Furthermore, this initiative concretely implements use cases being discussed and studied within the AI and RAN Working Group of the AI-RAN Alliance, such as coordinated operation of AI and RAN and dynamic allocation of computing resources.

Related Material (Published by the AI-RAN Alliance): AI-RAN Alliance Platform and Infrastructure Orchestrator White Paper

Next Steps

A demonstration of this technology is scheduled to be showcased at the Ericsson booth at MWC Barcelona 2026.

Building on the insights gained through this initiative, SoftBank and Ericsson will continue research, development, and demonstrations aimed at further advancing AI-RAN. Going forward, the two companies will continue to explore interfaces that support coordinated operation of AI and RAN, with the goal of realizing more flexible and efficient network operations.

Executive Comments

Ryuji Wakikawa, Vice President and Head of the Research Institute of Advanced Technology at SoftBank Corp., said: “Within AI-RAN, resources are no longer dedicated solely to RAN. GPU resources owned by the carrier are shared between RAN and AI, and centrally managed by the AI-RAN Orchestrator. When required, resources are dynamically allocated to RAN and seamlessly handed over to the SMO, which takes responsibility for RAN deployment and control. Establishing this integrated architecture between the AI-RAN Orchestrator and the SMO represents a significant step toward realizing AI-RAN.”

Jawad Manssour, President and Representative Director at Ericsson Japan K.K., said: “AI-and-RAN enables intelligence to be delivered into the network while enabling flexible and distributed orchestration. Through our collaboration with SoftBank, we are demonstrating how rApps (non-real-time RIC applications) and AI workloads can be harmonized and orchestrated together, unlocking new efficiencies and automation.”

*¹ SMO: An architecture defined by the O-RAN Alliance for network management and automation. It serves as a unified management platform that integrates configuration management of the Radio Access Network (RAN), performance optimization, and the execution management of applications (rApps), among other functions.

*² Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.

*³ O-Cloud is an open specification defined by the O-RAN ALLIANCE for platforms that host RAN applications.

*⁴ rApp is a cloud-based application that operates on the Non-Real-Time RIC (RAN Intelligent Controller) within the O-RAN architecture to enhance and optimize radio access networks using AI and other advanced technologies.