layer have been Near-RT and Non-RT RIC, considered at the SMO, and O-cloud network edge Benefits Several architectural Several deployment It addresses several frameworks based on options with AI/ML UCs and vertical C-RAN such as models to provide efficient industry requirements H-CRAN, V-CRAN, radio resource within the NG-RAN and F-CRAN to management (RRM), low architecture. It improve energy and latency, and real-time provides low latency spectral efficiencies processing and high processing and minimize latency services. Furthermore, and CAPEX/OPEX it provides a controller layer to obtain information regarding UEs such as energy, buffer, and link quality Limitations Overwhelming the The integration of some It provides different backhaul interface functionalities with deployment scenarios between the BBU and O-RAN is still in the early for each UC. In the CN, demanding stage such as addition, some fast fronthaul links self-organized network functions and and high round-trip (SON). In addition, E2E interfaces have not delay to process the control plane services still been defined by data of the end-user cannot be created by 5GPPP such as the devices by the cloud O-RAN [76] northbound interface (NBI) and southbound interface (SoBI) (CMRI) and so-called C-RAN. After that, several modifications and contributions have been proposed for C-RAN by Telecom bodies, e.g., Ericsson, ZTE, and Huawei. These contributions on C-RAN involve the deployment, advantages and challenges, architectures requirements, virtualization, and SO on. As presented in Table 1.3, several deployment scenarios have been implemented based on C-RAN involving V-CRAN, H-CRAN, and F-CRAN. However, six deployment scenarios have been considered for O-RAN based on the placement of the architecture components whether to be processed at the edge or cloud. On the other hand, C- M. Alfaqawi et al. RAN is composed mainly of RRHs and BBUs, while O-RAN and 3GPP classify the NG-RAN into RU, DU, and CU. The various architectures and state of the art for C-RAN, incl