Tag: DT

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.

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.

The concept of the Digital Twin (DT) has been around for years, but it has recently gained increased recognition. A Digital Twin is a software-based representation of a real-world system, device, or invention, designed to mimic its real-life counterpart as closely as possible. In this blog post, we explore the concept of DT and its potential impact on future networks. We highlight the benefits of using Network Digital Twins (NDTs) and demonstrate how integrating AI and ML with DT can enhance overall network performance. Additionally, we present the O-RAN ALLIANCE's perspective on DT and discuss potential future developments in this area.