Edge Caching and Resource Allocation Scheme of Downlink Cloud Radio Access Networks With Fronthaul Compression

With the rapid development of real-time applications in the Internet of Things, people have paid more and more attention on the traffic delay. Cloud radio access networks (C-RANs) are seen as a novel network architecture with significant advantages in reducing latency on control and data planes. In this paper, we aim to minimize the average user delay in a downlink C-RAN with a hierarchical structure of virtual controllers and high-speed but limited-capacity fronthaul links, by simultaneously considering edge caching, user association, and computing resource allocation. We first propose a caching scheme based on user preference and user mobility. Then the user association scheme is carried out according to the distances between users and remote radio heads. Finally, we reformulate the computing resource allocation problem as a matroid-constrained submodular function maximization problem and propose a heuristic scheme to find a sub-optimal solution. Besides, fronthaul compression technique is adopted to alleviate the capacity constraint of fronthaul links. Simulation results reveal that the proposed scheme achieves a better performance in terms of average system delay than three baseline schemes.