# 5G New Radio Open Radio Access Network Implementation in Brazil: Review and Cost Assessment
## 2 Background
### Open RAN Architecture
This separation enables multiple vendors to integrate their solutions using the same hardware and be hosted on COTS servers. The topology divides the vBBU into virtual Open RAN DUs (o-DUs) connected to virtual Open RAN CUs (o-CUs) through midhaul, with o-CUs linking to the core through the backhaul. In the fronthaul, enhanced CPRI (eCPRI) connects the o-DU to the RRU, supporting all wireless mobile generations from 2G to 5G and future generations. The Open-RAN Alliance publishes new RAN specifications, releases open software for the RAN, and supports participating institutions and members in their implementations. This architecture removes the vendor lock-in barrier, allows the integration of different solutions, and reduces the cost of implementation by fostering market competition among manufacturers. The elements utilize open, standardized interfaces, enabling a software-based, virtualized, flexible, intelligent, and energy-efficient network. The collected information facilitates the introduction of automated intelligence to the network through Artificial Intelligence (AI) and Machine Learning (ML). Control and User Plane Separation (CUPS) are functional RAN splits [2]. Network slicing leverages the SDN to manage resources using AI/ML, providing advanced controls through the RAN Intelligent Controller (RIC), making it possible to apply Quality of Service (QoS) and treat each traffic flow in the network differently [20]. The RIC oversees 5G network functions such as network slicing and prioritized communications and introduces programmable components with high-performance optimization and code-loop routines to control and orchestrate the virtual devices in the RAN. In addition, it can use several key performance measurements (KPMs) from the information collected on the infrastructure, process the data, and use AI/ML algorithms to automatically customize and optimize network resources [4]. It can intelligently manage mobility, admission control, and interference. The Near-Real-Time RAN IntelligentController (Near-RT RIC) optimizes tasks controlling RAN's resources, enhancing network resource utilization and user experience. It comprises custom logic applications called xAPPs that collect and process data and compute and return control actions to the resources. Near-RT RIC handles load balance, RB management, interference detection, and mitigation, leading to QoS management, connectivity management, and seamless handover control. The Non-Real-Time RAN Intelligent Controller (Non-RT RIC) includes configuration management, device management, fault management, performance management, and life cycle management for network elements, reducing manual intervention. Third-party applications called rAPPs manage the RAN optimization and control, adding value to the performance, including data analysis, resource configuration management, enrichment information, and policy guidance [4]. Another kind of application, dAPPs, can enable real-time control of the RAN nodes. They collect information from xAPPs to use RAN data that RIC cannot treat [21]. The evolution of mobile network architectures has been driven by the need to address the increasing demands for higher capacity, lower latency, and improved flexibility in network management. In this paper, we present a comparative analysis of four prominent RAN architectures: Open RAN, Cloud-RAN, Distributed RAN, and Virtualized RAN.