Cost-optimal network planning for converged optical X-haul in Beyond 5G networks

Abstract

The rapid evolution of wireless communication technologies has led to the development of Beyond 5G (B5G) networks, aiming to deliver ultra-low latency, high-capacity connectivity, and scalable deployments for applications including autonomous systems and immersive experiences. A critical challenge lies in efficiently designing the radio access network (RAN) and its transport infrastructure. The shift to open RAN (O-RAN) architectures, with disaggregated centralized units (CUs), distributed units (DUs), and radio units (RUs), offers a promising solution. However, optimal placement of these components and transport network design remains a challenge, especially in diverse and cost-sensitive environments. This paper proposes a comprehensive optimization framework for B5G network design, jointly optimizing the placement of O-RAN components and optical transport networks using Mixed Integer Linear Programming (MILP). By integrating geographic information system (GIS) data, the framework considers real-world constraints, including terrain, infrastructure, user distribution, coverage requirements, and capacity requirements, enabling practical and cost-effective designs. The proposed optimization framework allows exploration of the optimal planning solutions under diverse configurations, which helps analyze different network deployment approaches for their scalability and efficiency. The evaluation results demonstrate the effectiveness and versatility of the framework in reducing costs under diverse deployment scenarios while meeting performance and coverage requirements, offering valuable insights for network operators and planners.