Tag: ORAN

This blog demonstrates a complete approach to the utilization of the NDT for testing of RAN applications under the various scenarios and configurations, following the synthetic data generation approach. We describe the NDT workflow for creating a virtual replica of a live network based on the dataset provided by the MNO. Then we use this workflow to verify how Rimedo Labs rApps can improve its throughput, and reduce power consumption. The studies were performed on Rimedo’s NDT platform, fed with data from one of the leading MNOs, with a focus on two scenarios: a balanced network deployment and a social event scenario.

Rimedo Labs, together with i14y Lab, synthesized the standardization efforts from 3GPP, ETSI, and O-RAN ALLIANCE into the unified O-RAN E2E EE Testing Framework. The proposed framework brings SMO/Non-RT RIC and rApps into the equation, enabling evaluation of the tradeoff between running RAN automation algorithms and their impact on RAN. In this blog post, we demonstrate the implementation of the E2E EE Testing Framework in practice. We cover the PC measurements of multipleVNFs. We present the relevant tools and discuss the results obtained in i14y Lab while using a Dell R750 server hosting rApp Lab (a “Lightweight Non-RIC”) and communicating with Keysight RICTest emulating the RAN.

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.

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.

One approach to realize M-MIMO systems is the GoB concept which relies on a predefined set of beams that are launched in fixed directions. However, the main disadvantage of GoB is that the fixed set of beams may not track the dynamics of a real network, like users' mobility. In some cases, this can lead to QoS degradation. In this blog, we explore how to address this challenge by examining the concept of Beamforming Optimization in the context of its applicability. We present four use cases, with different approaches to the GoB, ranging from static to dynamic beam adaptation.

In this blog, we compare the synchronization source technologies and their potential for use in specific applications. We discuss the synchronization concepts in telecommunication, followed by a detailed explanation of synchronization in O-RAN, which deals with the fronthaul interface, its different configurations, and the timing requirements.