Environment-Aware Dynamic Management for Energy Saving in MIMO-Based C-RAN

Abstract

Energy consumption problem in wireless communication has attracted a lot of attention because of its ecological and economic benefits. Moreover, the energy consumption problem of wireless communication mainly derives from the base station. As the cellular networks are usually designed to satisfy the peak load but the network load varies with environment, much energy in the system is usually wasted. Many works have been done to improve the energy efficiency, but they have the following problems: 1) the system scenarios they adopted are not very practical-to be specific, not all of the emerging technologies are considered; 2) not all the adjustment schemes, i.e., BS sleeping, antenna switch, and power control, are considered, and; 3) they just consider the traffic fluctuations without other environment changes. Moreover, traffic volume is not obtained in real time but assumed in advance. Therefore, in this paper, we proposed an environment-aware dynamic management scheme in the transformium network architecture. In the scheme, we jointly apply the BS sleeping, antenna switch, and power control to dynamically adjust the network according to the environmental changes. The problem is considered in the multiple-input-multiple-output (MIMO)-based heterogeneous cloud radio access network (C-RAN) and formulated as a mixed integer programming problem. As it is NP-hard, we devise a heuristic algorithm to obtain the sub-optimal solution. The simulation results show that the proposed algorithm outperforms other baseline algorithms in system energy consumption and energy efficiency. The impact of some parameter settings is also analyzed. We set CthM=1,CthP=0.5 to achieve the balance between performance and complexity. Moreover, we analyze the BS sleeping strategy and the impact of rainfall.