Femtocell中基于负载预测的基站休眠节能方案

为达到5G中绿色节能通信的目标，在Femtocell网络下提出一种基于负载预测的基站节能方案。首先收集Femtocell基站（Femtocell base station，FBS）下的吞吐量数据，根据小数据量法证明其存在混沌特性，并对FBS的负载进行学习和预测；然后在负载预测的基础上定义吞吐量率，根据吞吐量率设计一种用户终端切换流程，以保证用户终端的通信服务质量和能效；最后，计算FBS的实时发射功率，并对FBS的发射功率做了预测和控制。仿真结果显示，该方案可以较为准确地预测FBS的吞吐量变化态势，并在此基础上的休眠节能方案也可以很好地提升系统的能效，减小整体能耗。

Energy-saving base station sleep strategy based on load prediction in Femtocell

In order to achieve the goal of green energy-saving communication in 5G, a Femtocell energy-saving sleep strategy based on load prediction is proposed under the Femtocell network. Firstly, the throughput data of FBS (Femtocell Base Station) is collected and chaotic characteristic of the data is verified according to the small-data method. In addition, the load of FBS is learned and predicted. Secondly, the throughput rate is defined on the basis of load prediction and user equipment switching process is designed according to the throughput rate to ensure the communication service quality and energy efficiency. Finally, the real-time transmit power of FBS is calculated and the transmit power of FBS is predicted and controlled. The simulation results show that our scheme can predict the throughput changing trend of FBS accurately, and the energy-saving sleep strategy can also improve the energy efficiency of the system and reduce the overall energy consumption.