The development of 6G wireless technologies is rapidly advancing, with the 3rd Generation Partnership Project (3GPP) entering the pre-standardization phase and aiming to deliver the first specifications by 2028. This paper explores the OpenAirInterface (OAI) project, an open-source initiative that plays a crucial role in the evolution of 5G and future 6G networks. OAI provides a comprehensive implementation of 3GPP and O-RAN compliant networks, including Radio Access Network (RAN), Core Network (CN), and software-defined User Equipment (UE) components. This paper details the history and evolution of OAI, its licensing model, and the various projects under its umbrella, such as RAN, the CN, and the Operations, Administration and Maintenance (OAM) projects. It also highlights the development methodology, Continuous Integration/Continuous Delivery (CI/CD) processes, and end-to-end systems powered by OAI. Furthermore, the paper discusses the potential of OAI for 6G research, focusing on spectrum, reflective intelligent surfaces, and Artificial Intelligence (AI)/Machine Learning (ML) integration. The open-source approach of OAI is emphasized as essential for tackling the challenges of 6G, fostering community collaboration, and driving innovation in next-generation wireless technologies.

Ob die SchülerInnen von „Fridays4Future“, die „Gelbwesten“ an den französischen Autobahnen, die FriedensaktivistInnen in der Türkei, die HausbesetzerInnen in den Metropolen – sie alle führen politische Kämpfe und üben sich dabei im Soziologisieren. Die Bewegungen führen vor, wie sich Sachprobleme mit Bezug auf ihre Gesellschaft artikulieren und bearbeiten lassen. Es scheint als würde heute die Soziologie weniger durch FachvertreterInnen, als vielmehr in diesen Protesten relevant gemacht. Im Folgenden wollen wir die verbreitete Praxis des Soziologisierens auf die andauernde, fachinterne Debatte um die „public sociology“ bzw. die Öffentlichen Soziologie beziehen.

In this work, we present and analyze methods and mechanisms for interconnecting a network slice control and management system of the mobile network, with an IEEE Time-Sensitive Network (TSN) control plane. IEEE TSN is gaining momentum as a key technology that is able to provide network service guarantees for Ethernet-based communications. Although Ultra-Reliable Low-Latency Communications (URLLC) have been thoroughly investigated in 5G, incorporating TSN technologies in the Transport Network is expected to unleash the potential of end-to-end deterministic communications, especially in industrial environments and time-critical applications like factory automation. We elaborate on the concepts of a TSN-aware Xhaul network, present a novel architecture, and describe a set of amendments required in order to enable network slicing. With the devised approach, a slice-aware TSN-enabled transport network can be controlled and managed in an end-to-end orchestrated way. Implementation experience and evaluation results are reported using TSN-enabled prototype devices, OpenAirInterface (OAI), and JOX slice orchestrator.

Network slicing is considered to be the enabler for a coexistence of a multitude of services with heterogeneous requirements on a multi-tenant 5G infrastructure. In the core network, it has shown its potential in customizing and extending service-specific functionality beyond a mere configuration. In the radio access network (RAN) however, service customization and functionality extension remain a challenge due to the rigid and complex nature of the RAN and the fact that all services have to be mapped onto the scarce radio resources. In this article, we present the RAN service engine that allows services to customize and extend RAN functionality using containerized micro-services. This is achieved through micro-SDKs that abstract key RAN control endpoints, and which can then be used by the services to flexibly customize and extend the RAN in order to steer control plane behavior. Through these micro-SDKs, the engine can enforce isolation between services while multiplexing them efficiently onto the infrastructure. We also present a concrete implementation of the engine with its key micro-SDKs, and demonstrate the feasibility through a prototype for the MAC scheduling control endpoint, showing the versatility of the RAN engine.

The 3rd Generation Partnership Project (3GPP) is investing a notable effort to mitigate the endogenous stack and protocol delays (e.g., introducing new numerology, through preemptive scheduling or providing uplink granted free transmission) to attain to the heterogeneous Quality of Service (QoS) latency requirements for which the fifth generation technology standard for broadband cellular networks (5G) is envisioned. However, 3GPP’s goals may become futile if exogenous delays generated by the transport layer (e.g., bufferbloat) and the Radio Link Control (RLC) sublayer segmentation/reassembly procedure are not targeted. On the one hand, the bufferbloat specifically occurs at the Radio Access Network (RAN) since the data path bottleneck is located at the radio link, and contemporary RANs are deployed with large buffers to avoid squandering scarce wireless resources. On the other hand, a Resource Block (RB) scheduling that dismisses 5G’s packet-switched network nature, unnecessarily triggers the segmentation procedure at sender’s RLC sublayer, which adds extra delay as receiver’s RLC sublayer cannot forward the packets to higher sublayers until they are reassembled. Consequently, the exogenously generated queuing delays can surpass 5G’s stack and protocol endogenous delays, neutralizing 3GPP’s attempt to reduce the latency. We address RLC’s related buffer delays and present two solutions: (i) we enhance the 3GPP standard and propose a bufferbloat avoidance algorithm, and (ii) we propose a RB scheduler for circumventing the added sojourn time caused by the packet segmentation/reassembly procedure. Both solutions are implemented and extensively evaluated along with other state-of-the-art proposals in a testbed to verify their suitability and effectiveness under realistic conditions of use (i.e., by considering Modulation and Coding Scheme (MCS) variations, slices, different traffic patterns and off-the-shelf equipment). The results reveal current 3GPP deficits in its QoS model to address the bufferbloat and the contribution of the segmentation/reassembly procedure to the total delay.

Unlike previous mobile networks, 5G New Radio (5G-NR) provides unprecedented flexibility in the radio access network (RAN) to support diverse use cases in a multi-tenant environment. In this context, the need for programmability and control through software-defined radio access networking (SD-RAN) is well established. While the underlying RAN is designed to be ultra flexible and lean, existing SD-RAN controllers are either not flexible to address all use cases or use a one-size-fits-all approach. In this paper, we present FlexRIC, a flexible and efficient software development kit (SDK) that enables to build specialized service-oriented controllers. FlexRIC has a modular architecture with minimal footprint and is designed with extensibility in mind. We validate the SDK building concrete implementations of two specialized controllers for state-of-the-art 5G use cases: (1) a recursive RAN controller that virtualizes the network to allow multiple tenants to concurrently control and operate their services in a shared infrastructure over the heterogeneous landscape of 5G networks, and (2) an SD-RAN controller providing programmability for multi-radio access technology (RAT) RAN slicing, and flow-based traffic control targeting low-latency communications. The results reveal that FlexRIC reduces the round-trip time by two while incurring 83 % less CPU compared with O-RAN's reference implementation, and uses 10x less CPU and one third of the memory when compared to FlexRAN. Such performance is required to unleash the potential of emerging 5G use cases.

Unlike previous mobile networks, 5G New Radio (5G-NR) provides unprecedented flexibility in the radio access network (RAN) to support diverse use cases in a multi-tenant environment. In this context, the need for programmability and control through software-defined radio access networking (SD-RAN) is well established. While the underlying RAN is designed to be ultra flexible and lean, existing SD-RAN controllers are either not flexible to address all use cases or use a one-size-fits-all approach.

AbstractNetwork slicing is one of the key enablers to provide the required flexibility for the envisioned service‐oriented 5G. We introduce a descriptor, a triple consisting of resources, processing, and state, as a means to describe base stations (BSs) and the embedded slices alike through a unifying description. Second, we propose a RAN slicing system, composed of the RAN runtime execution environment and accompanying controller based on this descriptor. This includes design and performance details of the employed system. Finally, we elaborate on the aspects of RAN slicing such as the radio resources, the processing chain of a slice, and its state.

In 5G radio access networks, meeting the performance requirements of the fronthaul network is quite challenging. Recent standardization and research activities are focusing on exploiting the IEEE Time Sensitive Networking (TSN) technology for fronthaul networks. In this work we evaluate the performance of Ethernet TSN networks based on IEEE 802.1Qbv and IEEE 802.1Qbu for carrying real fronthaul traffic and benchmark it against Ethernet with Strict priority and Round Robin scheduling. We demonstrate that both 802.1Qbv and 802.1Qbu can be well used to protect high-priority traffic flows even in overload conditions.

Network slicing is considered to be the enabler for a coexistence of a multitude of services on a multi-tenant 5G infrastructure. It is supported through software-defined radio access networking (SD-RAN), bringing programmability to the network in order to enhance performance according to the needs of slice owners. However, SD-RAN so far remained limited to a mere reconfiguration of the base station. In this work, we demonstrate a prototype of a service-oriented RAN on top of the OpenAirInterface and Mosaic5G platforms that brings programmability and extensibility to the RAN with a range of network applications for the purpose of intelligent slicing. We implemented a slice control and management framework, and plug a traffic analysis application that significantly improves the performance of slice users. We observe an improvement of 30% in application round-trip time with negligible variability for the considered traffic. Further, we demonstrate how to extend control plane functionality from a network store to improve slice performance.

The 5G mobile network is supposed to handle a variety of services with different requirements. By means of virtualization, network slices form customized virtual networks transporting services with associated service guarantees. Especially the radio access network (RAN) requires an efficient multiplexing of multiple services onto the sparse radio resources. In this demo, we show how a RAN can be dynamically customized without service interruptions for different slices. In particular, our solution considers the slice requirements and adapts the slicing algorithm without interrupting other slices in the network. This allows an efficient resource usage while respecting isolation and performance requirements, in particular latency. Furthermore, dynamic end-to-end slicing is enabled by automatically adding core networks as required by the slice owner. Finally, this solution allows to compare different slice algorithm implementations.

5G networks generate massive (quasi-) real-time data streams that different network apps can exploit to implement sophisticated single- or cross-domain control and management logic. This paper presents ElasticSDK, a Software Development Kit specially designed to abstract the development and chaining of such agile 5G monitoring apps for the control, management, and coordination of the underlying 5G network heterogeneous modules. Custom apps can collect, incrementally process and further expose flows in a flexible Pub/Sub fashion via appropriate SDK API calls, thus sharing both raw and complex data flows among themselves. Furthermore, the design of ElasticSDK allows respecting typical 5G data ownership and privacy models, as desired by the different 5G stakeholders ranging from physical infrastructure providers up to service providers over slicing. Finally, we provide two important contributions to the 5G open-source research community: (i) a RAN monitoring prototype implementation over the ElasticSearch and FlexRAN platforms that allows to demonstrate ElasticSDK app development and capturing hierarchical control features of typical SDN-enabled 5G architectures, and (ii) a first-ever publicly available dataset of realistic 5G RAN monitoring traces.

Future mobile networks are supposed to handle a variety of services with different requirements. Network slicing is considered to be a key enabler to cope with the increasing complexity of these networks. This includes slicing of the radio resources in order to use them efficiently. In this paper, we propose a radio resource slicing system for three types of slices with specific radio resource/quality of service (QoS) requirements. It enables co-existence of (1) rate-based/efficiency-oriented and (2) low-latency slices, as well as (3) slices with fixed allocations. Slice scheduling is based on utility functions with a priority-based resource allocation. Using simulations, we validate the applicability of the proposed system, and demonstrate that both a guaranteed throughput and low delay for different slices at the same time is possible. Our system outperforms existing slicing solutions in terms of delay requirement satisfaction and efficient resource utilization.

Alongside the mobile network evolution toward the fifth generation (5G) era, it is expected that the radio access network (RAN) will be the most challenging technology domain to serve multiple service requirements. Specifically, three critical aspects are particularly emphasized: (i) heterogeneous RAN deployments, (ii) RAN functional splits between disaggregated entities, and (iii) sliced RAN for multiple services. To synthesize these three different aspects, a unified and customizable control framework is needed to serve both needs of infrastructure provider and slice owner. To this end, we propose the FlexVRAN control framework as an extension to our previous work to provide a two-level abstraction scheme between the underlying physical infrastructures, logical base stations (BSs), and slice-specific virtual BSs. We present a proof-of-concept prototype of the proposed FlexVRAN over the OpenAirInterface (OAI) and FlexRAN platforms, and the evaluation results show the applicability and feasibility of software-defined RAN control over heterogeneous deployments in support of network slicing.

Online-Teilnehmer*innenvideos (OTV) werden im vorliegenden Beitrag als audiovisuelle Teilnehmer*innen-Accounts sozialer Situationen und Geschehnisse und zugleich als Bestandteile von sozialen Medien, Online-Videokultur und ihren technischen, medialen und sozialen Logiken gekennzeichnet. Dabei wollen wir zeigen, dass mit OTV ein vielschichtiger und sinnreicher Datentyp bereitsteht, der – genreabhängig – häufig ein Soziologisieren der Teilnehmer*innen dokumentiert und in der interpretativen Videoanalyse mit Gewinn genutzt werden kann. Gestützt auf die Erfahrungen aus Lehrforschungsprojekten, in denen mit diesem Datentyp v.a. im Kontext der Soziologie politischer Protestereignisse gearbeitet wurde, werden verschiedene Verfahrensschritte der Analyse von OTV vorgestellt. Dabei wird deutlich gemacht, dass die mit OTV gegebenen analytischen Möglichkeiten insbesondere im Bereich der interpretativen Soziologie des Affektiven liegen.

Flexibility is a key capability to allow future 5G networks to support varying service offerings over a common infrastructure. 5G-PICTURE investigates the design of programmable compute and transport network infrastructures, able to instantiate third-party 5G connectivity services on demand. This paper introduces the 5G-PICTURE vision on an integrated compute, RAN and transport architecture, and describes a set of innovative functions in the RAN, Transport and Synchronization domains that 5G-PICTURE has developed to fulfill its vision. Initial evaluation results are presented for the aforementioned functions.

Online-Teilnehmer*innenvideos (OTV) werden im vorliegenden Beitrag als audiovisuelle Teilnehmer*innen- Accounts sozialer Situationen und Geschehnisse und zugleich als Bestandteile von sozialen Medien, Online-Videokultur und ihren technischen, medialen und sozialen Logiken gekennzeichnet. Dabei wollen wir zeigen, dass mit OTV ein vielschichtiger und sinnreicher Datentyp bereitsteht, der – genreabhangig – haufig ein Soziologisieren der Teilnehmer*innen dokumentiert und in der interpretativen Videoanalyse mit Gewinn genutzt werden kann. Gestutzt auf die Erfahrungen aus Lehrforschungsprojekten, in denen mit diesem Datentyp v.a. im Kontext der Soziologie politischer Protestereignisse gearbeitet wurde, werden verschiedene Verfahrensschritte der Analyse von OTV vorgestellt. Dabei wird deutlich gemacht, dass die mit OTV gegebenen analytischen Moglichkeiten insbesondere im Bereich der interpretativen Soziologie des Affektiven liegen.

RAN slicing is one of the key enabler to enable virtualization of a BS and its delivery as a service with different levels of network isolation and sharing so as to accommodate the needs of mobile network operators and verticals. In this demonstration, we show a prototype of a RAN slicing run-time system to enable flexible slice customization on the top of a disaggregated RAN infrastructure [1] with different levels of isolation and sharing in terms of resources and network functions, while retaining the quality of service (QoS) for different slice instances. Furthermore, a novel plug & play network application chaining framework empowered by a network software development kit (SDK) is demonstrated to show how the multi-service programmability on per-slice basis can be achieved. Our demonstration is based on the OpenAirInterface [3], Mosaic-5G FlexRAN [4] and LL-MEC [2] platforms. Finally, we highlight how the the proposed approach can be extended to an end-to-end network slicing scenario.