Dynamic Resource Allocation With RAN Slicing and Scheduling for uRLLC and eMBB Hybrid Services
Lei Feng, Yueqi Zi, Wenjing Li, Fanqing Zhou, Peng Yu, Michel Kadoch
Abstract
To cope with the limited radio and power resources, designing energy- and cost-efficient resource allocation strategy with RAN slicing and scheduling is important in ensuring the extreme QoS of differentiated Internet of things (IoT) services. In this regard, we focus on guaranteeing the latency and reliability of sporadic uRLLC uplink traffic while improving the quality of continuous eMBB services (e.g., quality of the video) together in this paper. Firstly, a dynamic optimization model considering power consumption and service quality is used to construct the cost function in both time domain and frequency bandwidth for heterogeneous services, subject to the latency constraint. Secondly, given its complexity, a novel two-timescale algorithm with employing Lyapunov optimization is designed, including two sub-algorithms: long-timescale bandwidth allocation and short-timescale service control. In further, the theoretical optimality is analyzed according to the relationships between control parameters and service performances. The utility of our approach and its hard latency guarantee are also illustrated through simulation results under tolerable power consumption.