Multi-Service Network Slicing 5G NR Orchestration via Tailored HARQ Scheme Design and Hierarchical Resource Scheduling

<p><span>In the radio access network domain, novel applications' requirements and network dynamics claim scalable processing capabilities, decentralized architecture, and on-demand resource allocation. Due to the intrinsic heterogeneous nature of the network resources, a fully context-aware fronthaul management is extremely complex to design. Operators have a high level-of-abstraction of the infrastructure's resources, which limits their decision-making capabilities. In this paper, a novel radio access network orchestrator is proposed, which jointly combines network function placement and resource allocation techniques in a single optimization framework. Given the infrastructure and users' delay constraints, we formulate a constrained linear maximization problem to determine the optimal timing parameters of the downlink hybrid automatic repeat scheme for each user. At inter-slice layer, our proposed resource allocation method is modelled as a Markov decision process, where the resources' sharing policy is tailored according to the real-time slice traffic load. At the intra-slice level, under mild conditions the radio resources are strategically prioritized, following a game theoretic model. Simulation results show that our method performs the hybrid automatic repeat request response 37%–88% compared to the classical LTE schemes. The dynamic allocation method at the inter-slice level improves the resource's utilization up to 50% compared to static network slicing. Moreover, at the intra-slice, the under and over resource provisioning has been decreased by 21.35% and 60.08%, respectively, compared to the classical fair resource allocation schemes.</span></p>