Tag: rApp

Recently, the O-RAN automation market has been shifting toward the SMO/Non-RT RIC solutions. At the same time, due to the complexity of current systems, operators demand dynamic, intelligent, context-aware network automation. According to the O-RAN architecture, this can be realized by dedicated rApps residing in SMO/Non-RT RIC, typically utilizing AI/ML tools. This whitepaper provides an overview of the RAN automation with SMO and rApps. First, the SMO/Non-RT RIC architecture in O-RAN is introduced. It is followed by discussions on two promising use cases of RAN automation: traffic steering and beamforming optimization. The whitepaper addresses both general aspects and the design of related rApps, along with performance results.

In this blog post, we introduce the solution proposed by Rimedo Labs: Beamforming Optimization rApp (BO-rApp). We discuss how the BO-rApp can be improved when utilizing location information or a Network Digital Twin - a virtual replica of the network. Then, we point out a possible architecture for the BO-rApp within the O-RAN architecture.  Finally, we present numerical results demonstrating the benefits of the BO-rApp in an event-based scenario.

In this blogpost we are sharing results of our recent collaboration with VIAVI Solutions on rApps operation under live-network data. We show how we integrated our NDT solution with Viavi's Geolocation rApp, exposing the location-dependent datasets based on real-world network KPI. Having that in place, we put two of our key rApps to the test using real-world network data: COOS-rApp and TS-rApp. The results demonstrate what's possible when the advanced NDT meets real operational data.

In this blog, we discuss the results of the collaborative project focused on developing an rApp for traffic steering in 4G/5G heterogeneous RANs, leveraging an open-source O-RAN architecture. The SMaRT-5G initiative, involving industry partners like Intel Labs,  TietoEvry, Aether, VIAVI, and Rimedo Labs, experiments with SMO and Non-RT RIC hosting rApps - for coordinated network optimization. Here, we focus on migrating the TS function, originally designed as an xApp, to an rApp. The article covers the ideas, differences, the actual process of migration, and the final testing and integration of the TS-rApp.

This blog post discusses synthetic data generation for AI-based O-RAN xApps/rApps. We start by outlining the need for such data for O-RAN’s x/rApps training and testing. This is followed by the two preparation steps for synthetic data generation, namely, data alignment and data preparation. Finally, some opportunities and challenges are discussed.  

In the current heterogeneous mobile networks, traffic management is considered one of the key features to efficiently handle non-uniform user data. To realize this, the traffic steering function is employed, whose main task is to allocate users' traffic flows to network nodes or cells. O-RAN ALLIANCE provides means to support traffic steering through the utilization of Non- and Near-RT RIC frameworks and the accompanied rApps and xApps. This whitepaper provides an overview of the traffic steering topic in 5G mobile networks and how it fits into the O-RAN area. This is followed up by example implementations of the Traffic Steering xApp and its utilization for various use cases working in tandems with the corresponding rApps for energy saving and V2X scenarios.