Post-5G Blueprint¶
What is Post-5G ?¶
5G is an evolution of the cellular infrastructure that is based on 4 pillars, namely, cloud-native, softwarization, edge and finally, control and data plane separation. It has a transformative impact on openness and innovation.
SLICES proposes a post-5G blueprint in order to provide researchers with the ability to explore thought experiments in this domain. However, in order for our blueprint to be relatively easy to deploy, we recommend using a tested set of software and hardware components.
With this, researchers now have a rich platform for experimenting with new ideas at every level. Unfortunately, deploying a complete 5G infrastructure is complex, as every detail matters. Specialists are required to choose the correct combination of software, hardware, and infrastructure locations. This complexity can pull researchers away from their primary focus, as they may need to invest significant time and resources just to set up their experimental platform.
What is the Slices Post-5G Blueprint?¶
The Slices research infrastructure offers an ideal platform for experimenting with real hardware, ranging from low-end edge devices to high-end datacenter servers, distributed across multiple locations and interconnected by Layer 2 network links (with real or emulated network behavior).
The goal of the Post-5G blueprint is to provide the community with a replicable set of software, hardware, and methodologies for conducting experimental research in cutting-edge Post-5G environments.
This blueprint is designed in a modular way such that one can either deploy it fully or only partially. For example, researchers only interested in 5G can deploy the core and use a simulated RAN, whilst researchers interested only in the RAN can just deploy a RAN, assuming they have access to a core (e.g., via the SLICES central node or another partner). Advanced users can deploy both a core and multiple RANs. The blueprint also outlines a workflow to ensure reproducible research.
By integrating data storage, radio hardware (such as Radio Units and User Equipment), and supporting tools, this setup provides an ideal environment for Post-5G experiments. You can either use our OpenAirInterface-based solution or develop your own custom solutions. Experiments are orchestrated with the plain orchestrating service (POS) framework [0].
Built with increasing complexity, the blueprint is explained step-by-step and supported by an open-source reference implementation that serves as a baseline for researchers to conduct experimental research and for the SLICES community to build the SLICES infrastructure. The reference implementation can be found on the reference implementation git repository.
With the Post-5G blueprint service, we provide a step-by-step guide for defining a 5G environment and running experiments on it. This service automatically generates the necessary OpenAirInterface 1 configuration files, along with the POS scripts required to execute experiments on the SLICES-RI infrastructure. All experimental data and metadata are published in your personal SLICES DMI environment and can be easily found through the Metadata Registry System (MRS).
Note: This blueprint assumes that readers are familiar with 5G. A primer on 5G can be found in [2]. Reading the 3GPP TS 23.501 architecture is recommended [3] for engineers looking to deploy this blueprint in their infrastructure.
The Post-5G Blueprint offers templates and tutorials to assist researchers in utilizing this infrastructure for Post-5G research. It integrates essential components—such as the 5G core, RAN, data management, and radio resources—into streamlined, user-friendly experiments. This demonstrates how to effectively leverage the distributed Slices infrastructure for conducting Post-5G experiments.
What can I study with the Post-5G blueprint?¶
Type 1 studies: Vertical service integration and testing¶
Researchers can utilize the infrastructure as a layered architecture, treating it as a black box that provides a complete end-to-end service while still allowing them to understand the underlying components.
Example 1: Researchers use a Post-5G infrastructure to upload raw Lidar data from their drones to their ground station, enabling the creation of real-time 3D environment models. For these researchers, the scientific focus is on computer vision rather than telecom, so 5G serves merely as a commodity. Deploying such an infrastructure would be too costly and time-consuming for them.
Type 2 studies: Software Defined Networking¶
Researchers aim to modify the behavior of the network itself by adopting the Software Defined Networking (SDN) paradigm. They require complex environments to validate their findings.
SLICES provides access to well-defined network function interfaces (e.g., xAPP, P4, DPDK) and KPI collection.
Example 1: Researchers proposing AI-based dynamic placement of virtual network functions with performance guarantees must validate their algorithms on high-speed, operational-like networks. They require access to terabits-per-second backbones with programmable switches to test their implementations.
Type 3 studies: Low-level development on resources¶
Researchers focus on the lowest layers of the network stack (e.g., PHY/MAC) and must validate and measure their findings on actual hardware.
Example 1: Researchers developing a new low-energy MAC layer for high-density IoT locations with 5G gateways need access to real hardware to assess the performance of the new MAC and measure actual energy savings.
Type 4 studies: Novel hardware¶
Researchers explore new hardware technologies such as antennas, Reconfigurable Intelligent Surfaces (RIS), THz radio, cryptographic functions, packet processors, and TSN devices. This hardware is often not useful unless integrated into a complete system. Researchers can insert their hardware into the infrastructure and use their time slots for testing.
Example 1: Researchers have created a new Reconfigurable Intelligent Surface and must calibrate their model when integrated with 5G user equipment, where the 5G scheduler adapts communications based on real-time QCI feedback.
Type 5 studies: Cross-topics and resources¶
Researchers may require a combination of resources from various topics to succeed in their research.
Example 1: Researchers are creating a digital twin of a large interconnected radio network. Real-time 3D radio emulators operate on GPU farms, and the generated workload is interconnected over a Tbps P4 SDN core. The number of UEs in the radio networks makes it impractical to test with actual UEs, thus necessitating high processing capabilities linked directly to networking equipment.
Anatomy of an experiment¶
In the Post-5G blueprint, an experiment is organized into several key phases, each designed to ensure a smooth workflow. The first phase involves defining the experiment and its environment, which consists of a 5G Core Network (CN), a 5G Radio Access Network (RAN), and User Equipment (UE). The resources used can be either virtual or physical, such as a USRP acting as a gNB in the radio network. The SLICES-RI infrastructure supports this by providing a range of computing environments, including bare metal servers, Kubernetes clusters, and virtual machines, to meet diverse user needs.
Once the environment is established, the next step is to generate the experiment code, which is essentially a bash script that integrates various components to define the complete lifecycle of the experiment. This script governs the experiment’s execution by means of the POS framework, managing the interactions between different elements.
Since SLICES is a shared infrastructure, resource allocation requires a fair scheduling system. A calendar-based reservation service is used to manage resource access, ensuring fair distribution among experimenters. This calendar is integrated into the POS framework, which orchestrates the entire experiment, coordinating the execution of the experiment code on the required resources.
Upon completion of the experiment, all relevant data and metadata are collected and published in the Meta Data Registry System (MRS). The MRS serves to index the experiment results, linking them to the experiment’s code, making it possible to retrieve both the experimental outcomes and the corresponding code used for the run. This process ensures transparency and reproducibility, enhancing the value of the collected data for future reference.
flowchart TD A[fa:fa-pencil-ruler Experiment defintion] --> B B[fa:fa-file Experiment code generation] --> C C[fa:fa-calendar Book resources] --> D D[fa:fa-gears Experiment execution] --> E E[fa:fa-database Results publication]
Resources available for experimentation¶
SLICES provides a range of software and hardware resources designed for Post-5G experimentation. The central hub includes essential services for managing experiments, such as authentication, data management, webshell access, and an experiment orchestrator. It also features a Kubernetes cluster for deploying workloads. Across the continent, SLICES operates a network of nodes, each consisting of various sites that offer hardware resources, including radio equipment (e.g., USRPs, RRUs, UEs…), virtual machines, and bare-metal servers. These resources are interconnected through dedicated links over the Géant Network as shown in the diagram below.
graph TD central_hub <--> geant[Géant] geant<--> n1 geant<--> netc geant<--> nn subgraph central_hub [Central Hub] subgraph central_hub_k8s_cluster [k8s cluster] ch_w_1[Worker 1] ch_w_etc[...] ch_w_n[Worker N] end subgraph central_hub_s [Central Services] ch_s_1[Service 1] ch_s_etc[...] ch_s_n[Service N] end end subgraph n1 [Node 1] subgraph n1_s1 [Site 1] subgraph n1_s1_vms [Virtual machines] n1_s1_vm1[VM 1] n1_s1_vmetc[...] n1_s1_vmn[VM N] end subgraph n1_s1_bms [Baremetal machines] n1_s1_bm1[BM 1] n1_s1_bmetc[...] n1_s1_bmn[BM N] end end subgraph n1_setc [...] end subgraph n1_sn [Site N] subgraph n1_sn_vms [Virtual machines] n1_sn_vm1[VM 1] n1_sn_vmetc[...] n1_sn_vmn[VM N] end subgraph n1_sn_bms [Baremetal machines] n1_sn_bm1[BM 1] n1_sn_bmetc[...] n1_sn_bmn[BM N] end subgraph n1_sn_radio [Radio hardware] n1_sn_rru1[Radio Unit 1] n1_sn_rruetc[...] n1_sn_rrun[Radio Unit N] n1_sn_ue1[User Equipement 1] n1_sn_ueetc[...] n1_sn_uen[User Equipment N] end end end subgraph netc [...] end subgraph nn [Node N] subgraph nn_s1 [Site 1] subgraph nn_s1_vms [Virtual machines] nn_s1_vm1[VM 1] nn_s1_vmetc[...] nn_s1_vmn[VM N] end subgraph nn_s1_bms [Baremetal machines] nn_s1_bm1[BM 1] nn_s1_bmetc[...] nn_s1_bmn[BM N] end subgraph nn_s1_radio [Radio hardware] nn_s1_rru1[Radio Unit 1] nn_s1_rruetc[...] nn_s1_rrun[Radio Unit N] nn_s1_ue1[User Equipement 1] nn_s1_ueetc[...] nn_s1_uen[User Equipment N] end end subgraph nn_setc [...] end subgraph nn_sn [Site N] subgraph nn_sn_vms [Virtual machines] nn_sn_vm1[VM 1] nn_sn_vmetc[...] nn_sn_vmn[VM N] end subgraph nn_sn_bms [Baremetal machines] nn_sn_bm1[BM 1] nn_sn_bmetc[...] nn_sn_bmn[BM N] end end end
To conduct experiments, you access the system through a frontend interface. This frontend provides access to SLICES resources but is not designed to serve as a computational resource itself. Instead, for your experiments, you reserve specific resources such as a bare-metal server to deploy your gNB, a radio unit connected to the gNB to act as a radio heade and a user equipment to attach to this radio network, and, for example, deploy your 5G core in the kubernetes cluster of SLICES. Additionally, to manage and deploy the experiment, you allocate a separate compute resource, referred to as the deployment node, where the experiment is run and results are processed. As illustrated in the figure below, a virtual machine can be used as a deployment node for this purpose.
graph TD pos(Frontend) -->|reaches| n1_s1_vm1 subgraph central_hub [Central Hub] subgraph central_hub_k8s_cluster [k8s cluster] end end subgraph n1 [Node 1] subgraph n1_s1 [Site 1] subgraph n1_s1_vms [Virtual machines] n1_s1_vm1[VM 1 - **Deployment Node**] end end end subgraph nn [Node N] subgraph nn_sn [Site N] subgraph nn_sn_radio [Radio hardware] nn_sn_rru1[Radio Unit 1 **RRU** ] nn_sn_uen[UE N - **User Equipment**] end subgraph nn_sn_bms [Baremetal machines] nn_sn_bm1[BM 1 - **gNB**] end nn_sn_bm1 <-->|fiber| nn_sn_rru1 nn_sn_rru1 <-.->|radio| nn_sn_uen end end n1_s1_vm1 -.->|manages| central_hub_k8s_cluster n1_s1_vm1 -.->|manages| nn_sn_bm1 n1_s1_vm1 -.->|manages| nn_sn_rru1 n1_s1_vm1 -.->|manages| nn_sn_uen
The exact hardware can be found on the SLICES-RI resources repository.
The Post-5G Dashboard¶
To streamline the creation and execution of experiments, the Post-5G service provides a user-friendly dashboard. This dashboard includes a webshell that grants direct access to the SLICES infrastructure, allowing you to utilize all available resources—tools, software, and hardware—without needing to install anything on your local machine. Through the dashboard, you can also access the MRS to retrieve experiment-related metadata and data from a single location.
The SLICES Post-5G dashboard enables you to create experiment scripts and run Post-5G experiments entirely online. With just a SLICES account and a web browser, you can log into the Post-5G dashboard and start your work immediately, without any need for local software installations.
The dashboard features an assistant to guide you through defining your experiment’s 5G core and RAN settings, ensuring that the infrastructure meets your specific requirements. You begin by reserving the necessary hardware resources, such as servers, networking devices, or radio units, using a calendar-based resource reservation system.
Next, you configure the 5G infrastructure, specifying critical details like DNNs, slices, and the 7.2 split. You also define where to retrieve the experiment code that will be deployed on the infrastructure. The system then generates the required OpenAirInterface configuration, along with a POS experiment script to manage the execution on the SLICES platform.
When your reserved time slot arrives, you simply connect to the POS frontend and execute the automatically generated experiment script. Once the experiment is completed, all the data and metadata are stored in the DMI and made accessible via the MRS for easy discovery and future analysis.
Next steps¶
References¶
[0] Gallenmüller, S., Scholz, D., Stubbe, H. and Carle, G., 2021, December. The pos framework: a methodology and toolchain for reproducible network experiments. In Proceedings of the 17th International Conference on emerging Networking EXperiments and Technologies (pp. 259-266).
[1] OpenAirInterface | 5G software alliance for democratizing wireless innovation, [https://openairinterface.org/], accessed October 8, 2024.
[2] (1, 2) Peterson, L., Sunay, O., Davie, B., 2023. Private 5G: A Systems Approach, [https://5g.systemsapproach.org/], accessed December 12, 2023.
[3] ETSI, T., 123 501 V16. 6.0 (Oct. 2020). System architecture for the 5G System (5GS)
[4] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). [https://doi.org/10.1038/sdata.2016.18]