Open RAN is an emerging paradigm in mobile networks where the Radio Access Network (RAN) functions are disaggregated and virtualized on commodity servers. Despite the importance of Open RAN research, existing platforms often lack the fidelity and stability required to address a wide range of research problems. In response to this limitation, we have developed an enterprise-scale Open RAN testbed aimed at conducting state-of-the-art research in key areas that have received limited attention due to the lack of suitable platforms. In this poster, we provide an overview of the testbed we have created and examples of the research it has enabled, with the hope of catalyzing future open RAN research and innovation.

Open RAN, a modular and disaggregated design paradigm for 5G radio access networks (RAN), promises programmability through the RAN Intelligent Controller (RIC). However, due to latency and safety challenges, the telemetry and control provided by the RIC is mainly limited to higher layers and higher time scales (> 10ms), while also relying on predefined service models which are hard to change. We address these issues by proposing Janus, a fully programmable monitoring and control system, specifically designed with the RAN idiosyncrasies in mind, focused on flexibility, efficiency and safety. Janus builds on eBPF to allow third-parties to load arbitrary codelets inline in the RAN functions in a provably safe manner. We extend eBPF with a novel bytecode patching algorithm that enforces codelet runtime thresholds, and a safe way to collect user-defined telemetry. We demonstrate Janus' flexibility and efficiency by building 3 different classes of applications (18 applications in total) and deploying them on a 100MHz 4×4 MIMO 5G cell without affecting the RAN performance.

A key transformation of the Radio Access Network (RAN) in 5G is the migration to an Open RAN architecture, that sees the RAN functions virtualized and disaggregated. Open RAN, aims at accelerating innovation through the introduction of a programmable RAN Intelligent Controller (RIC). However, due to latency and safety challenges, the telemetry and control provided by the RIC is mainly limited to higher layers and time scales (>10ms), while also relying on predefined service models which are hard to change. In this work, we demonstrate Minerva, a programmable monitoring and control platform, specifically designed with the RAN idiosyncrasies in mind. Minerva introduces two novel components called Janus and Decima, for the deployment of safe RAN control and telemetry applications by trusted third-parties. Janus enables the deployment of codelets in the RAN functions using userspace eBPF for fast inline control and filtering of data. Decima, enables the deployment of sandboxed real-time control applications, by leveraging data collected from Janus and the OS. We demonstrate the benefits of Minerva through two applications related to interference detection and inter-cell interference mitigation, by leveraging a commercial-grade 5G testbed deployment.

State-of-the-art distributed in-memory datastores (FaRM, FaSST, DrTM) provide strongly-consistent distributed transactions with high performance and availability. Transactions in those systems are fully general; they can atomically manipulate any set of objects in the store, regardless of their location. To achieve this, these systems use complex distributed transactional protocols. Meanwhile, many workloads have a high degree of locality. For such workloads, distributed transactions are an overkill as most operations only access objects located on the same server - if sharded appropriately.

In this paper we study network architecture for unlicensed cellular networking for outdoor coverage in TV white spaces. The main technology proposed for TV white spaces is 802.11af, a Wi-Fi variant adapted for TV frequencies. However, 802.11af is originally designed for improved indoor propagation. We show that long links, typical for outdoor use, exacerbate known Wi-Fi issues, such as hidden and exposed terminal, and significantly reduce its efficiency.