The rapid evolution of wireless technologies has intensified interest in open and fully programmable radio access networks for whole-stack research, innovation, and evaluation of emerging solutions. Large-scale wireless living labs, such as ARA, equipped with real-world infrastructure play a vital role in this evolution by enabling researchers to prototype and evaluate advanced algorithms for next-generation wireless systems in outdoor and over-the-air environments benefiting from real-world fidelity and end-to-end programmability. However, at the core of this innovation is the performance in terms of coverage and reliability of these wireless living labs. For instance, interfacing power amplifiers and low noise amplifiers with software-defined radios (SDRs) for experimenting outdoors introduces issues in random access procedure—a process crucial in establishing connectivity between user equipment (UE) and the core network in 5G and 6G systems. Therefore, to ensure seamless connectivity and reliable communications in open-source 5G software stacks such as OpenAirInterface (OAI), we propose a slot-based approach to the 5G random access procedure leveraging full downlink (DL) and uplink (UL) slots instead of using special or mixed slots. We highlight how this approach achieves reliable 5G connectivity over 1 mile—the longest communication range that has been achieved so far in real-world settings using open-source 5G software stacks and the Universal Software Radio Peripheral (USRP) SDRs. We also demonstrate that, in a highly obstructed environment such as an industrial setting, we can increase the probability of a successful random access procedure to 90%–100% when we use at least 9 OFDM symbols to transmit msg2 and msg3.

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.

The third generation partnership project (3GPP) has defined ultra-reliable low latency communication (URLLC) as one of the key 5G competencies to provide high network reliability and low latency. The configured grant (CG) transmission, defined in 3GPP Release-15, is a technique that automatically transmits a URLLC packet with a configured number of repetitions to increase reliability. In this paper, we propose enhanced modeling for CG transmission considering the communication channel state to evaluate the network performance. The results show how to configure CG transmission to reach a defined probability of success for decoding the packets.

5G, the latest generation of cellular technology, targets not only enhanced data rates but also new applications which require, e.g., ultra-reliable low latency communication. Verticals like industrial automation or automotive, which want to make use of this type of wireless services, need experimental deployments to test the performance of 5G in various modes and environments for their use cases. Due to the ongoing stan-dardization process, experimental 5G networks based on open-source frameworks are especially well suited, as they provide the possibility to easily implement new features introduced by the yearly 5G standard releases. We thus present an experimental 5G standalone deployment, based on the OpenAirInterface, which is an open-source framework, that is being used both, commercially and for academic purposes. We evaluate coverage parameters including reference signal received power, reference signal received quality, and signal to interference and noise ratio both for single user and multiple user scenarios. The measured downlink data rate reaches up to 390 Mbps at a bandwidth of 60 MHz, which is close to the achievable theoretical value. The average latency both for uplink and downlink was measured to be 19 ms for the round trip time, while the minimum latency value was 6 ms, which is acceptable for many application.

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.

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.

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.

Dynamic spectrum access and management is one key enabler to constitute the foundation for a multi- service architecture with a high level of flexibility. In this work, we design and implement the spectrum management application (SMA) as an efficient tool to manage and process different policies and rules defined by various stakeholders such as national regulatory authorities, operators and licensed shared access. The SMA is an open- source and clean-slate replacement for legacy platform-dependent spectrum management solutions and can provide custom control programmability and agile resource utilization. We also elaborate on the design details of the SMA and show how it can dynamically select the optimal spectrum offers based on different applied rules in time-series. Finally, we demonstrate two specific use cases via integrating the implemented SMA prototype on top of the Mosaic5G and OpenAirInterface platforms.

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 runtime 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 OpenAirlnterface [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.