| Short name | Deliverable | Abstract |
|---|---|---|
| CLARION-E1 | Management and Dissemination of the project results | This document presents a comprehensive report on the activities and accomplishments of the 6G-CLARION subprojects in 2022 in relation to communication and dissemination. As the subprojects are interrelated, it was decided to combine the individual reports of each subproject into a single document.
In 2022, we experienced some delays in bootstrapping all activities due to the tender process. Despite this, we have achieved significant progress, which includes one paper contribution and an ongoing PhD thesis. |
| CLARION-NFD-E8 | Use cases definition (6G-CLARION-NFD) | RAN virtualization is expected to play a crucial role in the final phase of the next-generation mobile networks, with initiatives like the O-RAN alliance driving the adoption of this technology. However, the transition from dedicated to shared platforms may pose significant challenges due to the inherent computing fluctuations in wireless dynamics and resource contention in shared computing infrastructure. This can result in the price of migration being too high for some network operators. This document highlights the potential risks and deficiencies in the baseline architecture of a base station's distributed unit (DU), which can suffer from moments of deficit in computing capacity. To address these issues, we propose that a novel pipeline architecture specifically engineered for non-deterministic computing platforms, should improve the performance and reliability of 4G/5G DUs. Our proposed architecture can help to mitigate the risks associated with RAN virtualization and enable network operators to achieve optimal performance in their networks. In this document, we present a strong case for the adoption of our proposed pipeline architecture for 4G/5G DUs on non-deterministic computing platforms. |
| CLARION-OR-E8 | Use cases definition (6G-CLARION-OR) | The rise of softwarization and cloudification in network functions presents a vast opportunity for the next generation of mobile networks. However, to fully exploit the potential of flexible network architectures to meet the ever-increasing service demands and requirements, it is crucial to effectively integrate Network Intelligence (NI) solutions into production infrastructures. While standardization efforts in this area are still in their infancy, cutting-edge initiatives are taking the native NI orchestration into account. In this paper, we present a general model for the representation of NI instances that facilitates their integration into network environments. We showcase the practical viability and benefits of this approach by analyzing two state-of-the-art Network Intelligence algorithms implemented in an open-source data flow programming framework. |
| CLARION-SI-E8 | Use cases definition (6G-CLARION-SI) | Network technologies are embracing the cloud-native paradigm, following the current best practices in cloud computing. Cloud-native technologies might be applied to different types of network functions in a mobile network, but they are particularly relevant nowadays for core network functions, as the recent standard introduces the Service-Based Architecture that matches modern cloud-native technologies such as Docker or Kubernetes. In parallel, a number of open source software initiatives already provide researchers and practitioners with usable software that implements the key functionality of a mobile network (both for LTE and 5G). These software solutions, however, are monolithic and not integrated into state-of-the-art cloud native frameworks. In this paper, we fill this gap by describing the implementation of a cloud-native mobile network, which supports channel emulation and provides an affordable and scalable way of testing orchestration algorithms with standardized VIM interfaces. |
| CLARION-OE-E12 | Use cases definition (6G-CLARION-OE) | The integration of network operation and network service provisioning with the advent of 5G has highlighted the limitations of current network architectures in providing means for such integration. Existing mobile network designs only allow for continuous optimization within specific domains, resulting in a "silo-style" automation that falls short when aiming for closed-loop automation. In this work, we analyze the feasibility of a network-wide capability exposure framework for closed-loop automation by analyzing the producing domains and the different capabilities that shall be exposed by each of them. |
