Computing Resource Aware Energy Saving Scheme for Cloud Radio Access Networks

Cloud radio access network (Cloud-RAN) has been recognized as one of the most promising architectures for next generation wireless network. The features of Cloud-RAN include the central signal processing mechanism and the flexible information interaction among cloud platforms. The General Purpose Processors (GPP) are a more efficient to multiplex computing resource in the cloud platform. In this paper, we study the impact of the computing resource sharing on the total power consumption in downlink Cloud-RAN. Aiming to minimize the total power consumption of Cloud-RAN, we formulate the optimization problem with the consideration of the power consumption in the cloud platform, fronthaul links and base stations. By leveraging the iterative l(0) approximation method, we transform the optimization problem into a second-order conic programming (SOCP) problem. Then, we propose a two-loop iterative algorithm to obtain the optimal solution. Simulation results show that the proposed algoritlun significantly reduces power consumption of Cloud-RAN as compared to the static resource allocation algorithm. The simulations also validate that the GPP-based Cloud-RAN achieves better power consumption performance as compared to the traditional network and Virtual Base Station (VBS)-based network.