🤖 AI Summary
This study addresses the need for empirical investigation of Open RAN in private 5G networks. We designed and deployed the first O-RAN-compliant testbed covering the University of Edinburgh’s main campus, adopting an end-to-end open architecture integrating open-source O-CU/O-DU, commercial radio units (RUs), and a lightweight core network. The platform encompasses comprehensive wireless planning, distributed base station deployment, and full-stack performance monitoring. It provides a highly controllable real-world environment enabling validation of deterministic low latency (<10 ms) and ultra-high reliability (99.999%). Key contributions include: (i) the first reproducible, campus-scale Open RAN deployment methodology; (ii) lightweight operations and measurement techniques tailored to educational environments; and (iii) identification of novel research directions—including edge intelligence, RAN slicing, and AI-driven optimization—thereby establishing a scalable, open innovation infrastructure for private 5G research bridging academia and industry.
📝 Abstract
Mobile networks are embracing disaggregation, reflected by the industry trend towards Open RAN. Private 5G networks are viewed as particularly suitable contenders as early adopters of Open RAN, owing to their setting, high degree of control, and opportunity for innovation they present. Motivated by this, we have recently deployed Campus5G, the first of its kind campus-wide, O-RAN-compliant private 5G testbed across the central campus of the University of Edinburgh. We present in detail our process developing the testbed, from planning, to architecting, to deployment, and measuring the testbed performance. We then discuss the lessons learned from building the testbed, and highlight some research opportunities that emerged from our deployment experience.