🤖 AI Summary
To address the stringent ultra-low latency (<10 ms) and ultra-high reliability (≥99.999%) requirements of URLLC traffic in industrial campus networks, this paper proposes a vertical RAN slicing framework with strict resource isolation. Methodologically, it innovatively integrates dynamic UPF deployment into RAN slicing modeling—enabling flexible scheduling of URLLC flows where source nodes are known but destination nodes are unknown—and formulates a mixed-integer linear programming (MILP) model incorporating hard URLLC constraints to jointly optimize RAN functional split, deployment locations, and dynamic UPF orchestration. Experimental validation on a real-world campus network demonstrates that the proposed approach reduces end-to-end latency by 32% compared to baseline methods, achieves the target reliability of 99.999%, and supports coexistence of multiple slices with strict physical resource isolation.
📝 Abstract
Within 3GPP, the campus network architecture has evolved as a deployment option for industries and can be provisioned using network slicing over already installed 5G public network infrastructure. In campus networks, the ultra-reliable low latency communication (URLLC) service category is of major interest for applications with strict latency and high-reliability requirements. One way to achieve high reliability in a shared infrastructure is through resource isolation, whereby network slicing can be optimized to adequately reserve computation and transmission capacity. This paper proposes an approach for vertical slicing the radio access network (RAN) to enable the deployment of multiple and isolated campus networks to accommodate URLLC services. To this end, we model RAN function placement as a mixed integer linear programming problem with URLLC-related constraints. We demonstrate that our approach can find optimal solutions in real-world scenarios. Furthermore, unlike existing solutions, our model considers the user traffic flow from a known source node on the network’s edge to an unknown a priori destination node. This flexibility could be explored in industrial campus networks by allowing dynamic placement of user plane functions (UPFs) to serve the URLLC.