The fifth-generation mobile evolution introduces Next-Generation Radio Access Networks (NG-RAN), splitting the RAN protocol stack into the eight disaggregated options combined into three network units, i.e., Central, Distributed, and Radio. The disaggregated units reach full interoperability on Open RAN. Further advances allow the RAN software to be virtualized (vNG-RAN) on top of general-purpose hardware, enabling the management of disaggregated units and protocols as radio functions. The placement of these functions is challenging since the best decision must be based on multiple constraints, e.g., the RAN protocol stack split, routing paths in network topologies with restricted bandwidth and latency, asymmetric computational resources, etc. The literature does not deal with general placement problems with high functional split options and protocol stack analysis. This article proposes the first exact model for positioning radio functions for vNG-RAN planning, named PlaceRAN, as a Binary Integer Linear Programming (BILP) problem. The objective is to minimize the computing resources and maximize the aggregation of radio functions. The evaluation considered two realistic network topologies, and the results reveal that PlaceRAN achieves an optimized high-performance aggregation level. It is flexible for RAN deployment overcoming the network restrictions, and up to date with the most advanced vNG-RAN design and development.

The fifth-generation mobile evolution enables Next-Generation Radio Access Networks (NG-RAN) transformations. The RAN protocol stack is split into eight disaggregated options combined in three network units, i.e., Central, Distributed, and Radio. Further advances allow the RAN functions to be virtualized on top of general-purpose hardware using the virtualized RAN (vRAN). The combination of NG-RAN and vRAN results in vNG-RAN, enabling the management of the disaggregated units and protocols as a set of radio functions. However, the orchestration-based placement of these radio functions is challenging since the best decision can be determined by multiple constraints involving RAN disaggregation, crosshaul network requirements, availability of computational resources, etc. This article proposes OPlaceRAN, a vNG-RAN deployment orchestrator framed within the NFV reference architecture and aligned with the Open RAN initiative. OPlaceRAN supports the dynamic placement of radio functions focusing on vNG-RAN planning and is designed to be agnostic to the placement optimization solution. We developed a prototype based on cloud-native tools to deploy RAN using containerized virtualization and the OpenAirInterface emulator. The evaluation is analyzed considering two different approaches as a proof-of-concept. First, we applied two placement solutions in a controlled real computing infrastructure with a crosshaul network. Second, we investigated the orchestrator’s scalability with a real and larger-scale topology. Our results show that OPlaceRAN is an effective cloud-native solution for containerized network function placement and agnostic to the placement solution, handling scale-out well. OPlaceRAN is up-to-date with the most advanced vNG-RAN design and development approaches, contributing to the evolution of fifth-generation networks.