Delay-Aware Radio Resource Allocation Optimization for Network Slicing in Fog Radio Access Networks

Abstract

Fog radio access networks (F-RANs) take full advantages of both fog and cloud computing technologies, and benefit from using network slicing to support diverse services with different quality-of-service (QoS) requirements. In this paper, to make the network slicing in F-RANs work efficiently, the radio resource allocation for different network slices is exploited in a downlink F-RAN with device-to-device communication, which is logically partitioned into a high-transmission-rate slice and a low-latency slice. A multi-objective optimization problem is presented with respect to diverse QoS demands, which can be formulated as a single-objective optimization problem with a linear weighted sum method. Then an equivalent drift-plus-penalty minimization problem with Lyapunov optimization is proposed, in which two subproblems are partitioned and solved by weighted minimum mean square error approach and Lagrange dual decomposition method, respectively. Numerical results confirm that a [O(1/V),O(V)] utility-delay tradeoff is obtained, in which either a 34.5% reduction in the queuing delay or a 6.5% increase in the average weighted utility can be achieved in a specific model by choosing proper values of V.