###### Abstract  
With the advent of 5G networks, the demand for improved mobile broadband, massive machine-type communication, and ultra-reliable, low-latency communication has surged, enabling a wide array of new applications. A key enabling technology in 5G networks is network slicing, which allows the creation of multiple virtual networks to support various use cases on a unified physical network. However, the limited availability of radio resources in the 5G cloud-Radio Access Network (C-RAN) and the ever-increasing data traffic volume necessitate efficient resource allocation algorithms to ensure quality of service (QoS) for each network slice. This paper proposes an Adaptive Slice Allocation (ASA) mechanism for the 5G C-RAN, designed to dynamically allocate resources and adapt to changing network conditions and traffic delay tolerances. The ASA system incorporates slice admission control and dynamic resource allocation to maximize network resource efficiency while meeting the QoS requirements of each slice. Through extensive simulations, we evaluate the ASA system's performance in terms of resource consumption, average waiting time, and total blocking probability. Comparative analysis with a popular static slice allocation (SSA) approach demonstrates the superiority of the ASA system in achieving a balanced utilization of system resources, maintaining slice isolation, and provisioning QoS. The results highlight the effectiveness of the proposed ASA mechanism in optimizing future internet connectivity within the context of 5G C-RAN, paving the way for enhanced network performance and improved user experiences. 5G; radio access network; network slices; Cloud-RAN slicing; dynamic resource allocation; slice admission control +
Footnote †: journal: Future Internet  
excellent dependability to enable time-sensitive applications like e-health, smart cities, and smart autos. Furthermore, the mMTC use case necessitates a sizable network capacity to accommodate numerous connections from low-power devices, like those used in IoT software. The specifications for these 5G applications are detailed in Table 1.  
Scientists have put forth a lot of time and effort to develop 5G-compatible devices. Software-defined networks (SDN), network function virtualization (NFV), mobile edge computing (MEC), and cloud radio access network (C-RAN) methods are all examples of such critical enabling technologies [2]. C-RAN design is used in 5G networks to handle the growing number of connections with varying quality of service needs. Baseband units (BBUs) are decoupled from physical base stations to build a virtual centralized BBU pool as part of our investigation of a two-layer, fully centralized C-RAN architecture. The BBU pool processes and allocates the radio resources on demand [5; 6], as it is responsible for all the functions of the physical, MAC, and network layers. The 5G networks introduce the idea of network slicing, which helps vertical businesses meet their varied needs. With network slicing, a single physical infrastructure can be partitioned into many, autonomous virtual slices, each of which can have its own set of performance characteristics and set of resources [7]. Network functions virtualization (NFV) and software-defined networking (SDN) are just two examples of the technologies that have helped with the creation and management of virtual functions in network slices. In particular, the network slices in 5G C-RAN are able to handle their requests and distribute resources with greater flexibility because to the virtualization of BBU functions [8; 9]. Through network slicing, individual 5G use cases can be allocated their own dedicated slice of the network, with their own set of quality-of-service settings. The C-RAN, the transport network, and the core network are all included in the end-to-end network slices it creates [4]. End-to-end slicing has been the subject of extensive research, particularly in the context of the central network. For the purpose of this study, we isolate the topic of network slicing in C-RAN.