tures in Sect. 1.2 are classified into cloud-based and edge-based frameworks. In Sect. 1.2.1, several cloud-RAN (C-RAN) architectural frameworks are reviewed including centralized and partially C-RAN, H-CRAN, and V-CRAN. In Sect. 1.2.2, 5G edge cloud architectural frameworks are investigated involving F-CRAN, O- RAN, and NG-RAN with MEC. These architectural frameworks are compared in Sect. 1.2.3 in terms of deployment scenario, architecture differences, benefits, and limitations. Section 1.3 addresses the architectural frameworks and spectrum options for private 5G networks. Section 1.3.1 presents the proposed architecture classifications by MNOs for private 5G networks including non-public network (NPN) and shared- RAN. In addition, Sect. 1.3.2 highlights the spectrum options for industry and private 5G networks including shared and unlicensed spectrum. Section 1.4 investigates the key 5G enabling technologies including SDN, NFV, network slicing, AI/ML, and MEC. In Sects. 1.4.1 and 1.4.2, the concept, architectural framework, benefits, challenges, and recent research works on SDN and NFV, respectively, are explored. Then, in Sect. 1.4.2, network slicing is discussed involving concept, architecture, benefits, and challenges. After that, Sect. 1.4.3 presents AI/ML strategies and methods and 5G UCs to integrate AI/ML. Furthermore, recent AI/ML research works are reviewed to tackle 5G challenging issues. Section 1.4.4 highlights MEC within 5G technology including concept, benefits, architectural framework, and research works. Section 1.5 presents software (SW) and projects in 5G research and development (R&D). Section 1.5.1 explores and compares the features of several development platforms and SW including OpenAirInterface (OAI), network simulator-3 (NS-3), and MATLAB. Then, Sect. 1.5.2 reviews two 5G projects to provide programmable, flexible, and agile 5G services. Lastly, Sect. 1.6 summarizes the contribution of this chapter including challeng- ing issues on 5G technology. M. Alfaqawi et al. 1.2 5G Architecture 