The O-RAN Software Community (SC) Documentation.

Welcome to O-RAN SC N Release Documentation Home

About O-RAN Software Community (SC)

Who We Are

The O-RAN Software Community (SC) is a collaboration between the O-RAN Alliance and the Linux Foundation with the mission to support the creation of software for the Radio Access Network (RAN). The RAN is the next challenge for the open source community. The O-RAN SC plans to leverage other LF network projects while addressing the challenges in performance, scale, and 3GPP alignment.

Mission

Manage all software development, code storage, tooling, and developer integration testing aligned with the architecture specified by the O-RAN Alliance.

Vision

The telecom industry is experiencing a profound transformation, and 5G is expected to radically change how we live, work, and play. It’s critical to make network infrastructure commercially available quickly to ensure business success for operators. Turning to open source is one of the most efficient ways to accelerate product development collaboratively and cost-efficiently.

The O-RAN Software Community aligns with the O-RAN Alliance’s open architecture and specifications to achieve industry deployment solutions. Sponsored by the O-RAN Alliance, this new open source community under the Linux Foundation will develop modular, open, intelligent, efficient, and agile disaggregated radio access networks.

Get Involved

You can get started by joining the mailing list and Technical Oversight Community (TOC) meetings.

Project Scope & Goals

Software development, documentation, testing, and integration. Coordinate with related open source software projects and standards communities. Align with O-RAN architecture.

New features in N release:

Near-Real-time RIC X-APPs (RICAPP)

RICAPP N Release Feature Scope:

Maintain existing xApp’s to the N Release

Near-Real-time RAN Intelligent Controller Platform (E2 Interface) (RICPLT)

RICPLT N Release Feature Scope:

No new code changes, only bug fixes.

Non-Real-time RIC (NONRTRIC)

NONRTRIC N Release Highlights:

Continue support & improvements for SMO integration - with updated version of a fully integrated SMO deployment blueprint (See Integration & Test project below)

Maintained/Supported existing NONRTRIC/SMO platform functions

Continued development & improvement of SMO/NONRTRIC/rApp use cases

Improved robustness and specification compliance.

Improved Testing & End-to-end Integration

Assisted in Jenkins → GHA migration

Documentation tooling update

Upgrade Java-based Docker base images to recent versions

Operation and Maintenance(OAM)

OAM N Release Feature Scope:

Simplification of deployment by removing ONAP DMaaP

Integration of fail based PM in docker compose deployment.

Integration of grafana into user management solution by keycloak

Status information within topology

updates of images used in docker-compose deployments to reduce CVEs in deployments

O-DU High

O-DU High N Release Feature Scope:

Integration of ODU-High with intel L1

OSC-OAI Collaboration

Adapting to New ASN.1 encoder decoder

O-DU Low

O-DU Low N Release Feature Scope:

Integration with ODUHIGH

Simulators (SIM)

SIM N Release Feature Scope:

Keep alignment with latest O-RAN specifications (O1, E2)

Focus on hybrid and hierarchical OAM architecture (O-DU O1 interface simulator and O-RU OpenFronthaul M-Plane interface simulator)

Infrastructure (INF)

INF N Release Feature Scope:

Update INF StarlingX O-Cloud to aligned with StarlingX 12.0

Update O2 implementation to aligned with new Spec

Update the support for OKD O-Cloud

Service Management and Orchestration (SMO)

SMO M Release Feature Scope:

Topology Exposure & Inventory (TEIV)

Improve O2 DMS ETSi profile.

Intelligent LCM with integration DMS, NFO and RIC

Improve the NFO K8s profile integration with OSC-INF.

Integration(INT)

INT N Release Feature Scope:

Have AIMLFW + SMO + Non-RT RIC + OAM integrated into a single cluster vanilla k8s

AI/ML Framework(AIMLFW)

AI/ML Framework N Release Feature Scope:

Generic and composable pipeline, qoe-pipeline use case has been broken down to reusable components.

New repository has been added to provide SDK for pipeline preparation.

Four reusable component has been introduced: feature extraction, model training, model storage, model metrics storage (Note: Functionality not yet implemented)

Model storage SDK enhanced to exchange data between components.

Error Handling for responses as per the specification.

Fix APIs for fetching and storing model metrics.

Fix external model upload.

Model storage SDK could be executed in standalone mode (without kubernetes).

Abstraction for different storage mechanism has been added to model storage SDK.

Please find some guidance here on the content of O-RAN SC documentation.

Contents:

User experience

Here are some O-RAN SC user experience

Indices