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The 5G standard is aimed at supporting Quality of Service (QoS)-constrained traffic types, enabling new services to be reliably built into scenarios such as industrial automation and smart cities. The support comes via a strong emphasis on resource virtualization in the form of slices. Due to the strong QoS constraints of each slice, determining how to actually split the radio resources among different slices, while considering simultaneously the priority of slices, network efficiency, and each slice&#x0027;s target QoS, is very challenging. In this paper, we propose a radio resource scheduling scheme, designed on the basis of a strong theoretical analysis, to address the challenges. We formulate a Chance-constrained optimum resource allocation problem, which is then converted into a low complexity deterministic knapsack problem utilizing the concept of effective bandwidth. The performance analysis proves that our proposal is better in efficiency than the existing schemes, under different network conditions and QoS constraints. Results clearly show the effectiveness of our scheme in the considered 5G scenarios.

A QoS Improving Downlink Scheduling Scheme for Slicing in 5G Radio Access Network (RAN)