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.

Driven by the key principles of open interfaces, virtualization and programmability, Open RAN has emerged as a new paradigm to evolve contemporary Radio Access Networks (RANs) into a more vendor-agnostic, softwarized, and intelligent ecosystem. To this end, Software Defined RAN (SD-RAN) initiatives (e.g., O-RAN) are drafting specifications to provide the means to embrace it. However, even though O-RAN following the Open RAN paradigm specifies Service Models (SMs) to monitor and control the RAN, it does not go beyond the Quality of Service (QoS) mechanisms provided by 3GPP. Therefore, the QoS degradation that occurs mostly due to data flow’s nature at the slowest data path link (e.g., high L2 sublayers), is not addressed by contemporary O-RAN SMs. In this paper, we present a traffic control system for SD-RAN, denoted as TC-RAN, that consists of an E2 service Model (E2SM) and a RAN Function (RF) that adheres to the Open RAN principles and promotes data flows to first-class citizens in cellular networks, upgrading contemporary 5G QoS mechanism. TC-RAN introduces a 6 programmable, extendable, and customizable pipeline composed of a classifier, a policer, a queue, a scheduler, a shaper and a pacer. Additionally, TC-RAN addresses QoS degradation scenarios unsolvable through Resource Block (RB) allocation or 3GPP slicing mechanisms, unleashing the true potential for deploying extremely demanding applications and creating a green field for AI/ML cross-optimization algorithms on the road to 6G. We prototype and validate TC-RAN in a real 5G Stand Alone (SA) RAN stack using an O-RAN compatible near Real-Time Radio Intelligent Controller (nearRT-RIC), xApps, and Commercial off-the-shelf (COTS) User Equipments (UEs). The results show that intelligently composing a TC-RAN pipeline in cellular networks can considerably reduce the latency, notably enhancing the Quality of Experience (QoE) in a real multiplayer online game.

RAN openness is a vision for 5G and beyond to avoid unnecessary lock-in effects. In this regard, the O-RAN alliance provides a new architecture with RAN intelligent controller (RIC) for both non-real-time and near-real-time cases, together with running applications, i.e., rApps and xApps. However, two key challenges remain in the current xApp framework: platform lock-in and xApp reusability. Therefore, we introduce a novel FlexApp framework to address both issues, as well as a new E2* interface that consumes less latency and CPU utilization. This new interface speeds up the xApp development process. Our performance evaluation of the FlexApp prototype shows that it can realize scalability and ultra-low latency operations (<10 ms), as well as the capability of two-level abstraction for xApp development.

3GPP standards organization is performing an impressive effort trying to reach sub-millisecond latencies for 5G. However, such efforts may become fruitless if exogenously generated delays at transport layer are not considered. Nowadays, Radio Access Networks (RANs) are deployed with large buffers to achieve full utilization and avoid squandering wireless resources. Unfortunately, and since the data path’s bottleneck resides on the radio link, RAN’s buffers are bloated by TCP’s congestion control algorithm. Thus, a flow with low-latency requirements that encounters a bloated buffer, suffers from inevitable large sojourn times associated with the buffer depletion time, severely downgrading its Quality of Service (QoS). This paper presents different solutions for efficiently multiplexing distinct traffic patterns that share buffers on the 5G stack. Bufferbloat is extensively studied within the actual 5G QoS scenario, which presents multiple challenges inherited from the dynamic radio link nature and the presence of multiple queues at different entities. We propose and extensively emulate different algorithms in order to avoid the exogenous delay caused by the bufferbloat phenomena. We use real cellular network traces with realistic delay-sensitive and background traffic patterns in different scenarios. The outcome presents valuable insights in the algorithms that will enable low-latency services to be delivered through the 5G network stack satisfying restrictive envisioned constraints.

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.