A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage.It is a key technology for the new generation of the mobile communication system.The dense deploymen...A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage.It is a key technology for the new generation of the mobile communication system.The dense deployment of small base stations not only improves the quality of network service,but also brings about a significant increase in network energy consumption.This paper mainly studies the energy efficiency optimization of the Macro-Femto heterogeneous cellular network.Considering the dynamic random changes of the access users in the network,the sleep process of the Femto Base Stations(FBSs)is modeled as a Semi-Markov Decision Process(SMDP)model in order to save the network energy consumption.And further,this paper gives the dynamic sleep algorithm of the FBS based on the value iteration.The simulation results show that the proposed SMDP-based adaptive sleep strategy of the FBS can effectively reduce the network energy consumption.展开更多
基金This work was supported by the Program for the National Science Foundation of China(61671096)the Chongqing Research Program of Basic Science and Frontier Technology(cstc2017jcyjBX0005)+1 种基金Chongqing Science and Technology Innovation Leading Talent Support Program(CSTCCXLJRC201710)Venture and Innovation Support Program for Chongqing Overseas Returnee.
文摘A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage.It is a key technology for the new generation of the mobile communication system.The dense deployment of small base stations not only improves the quality of network service,but also brings about a significant increase in network energy consumption.This paper mainly studies the energy efficiency optimization of the Macro-Femto heterogeneous cellular network.Considering the dynamic random changes of the access users in the network,the sleep process of the Femto Base Stations(FBSs)is modeled as a Semi-Markov Decision Process(SMDP)model in order to save the network energy consumption.And further,this paper gives the dynamic sleep algorithm of the FBS based on the value iteration.The simulation results show that the proposed SMDP-based adaptive sleep strategy of the FBS can effectively reduce the network energy consumption.
文摘5G宏基站(base station,BS)节能优化是移动通信行业践行绿色低碳发展、实现碳中和目标的重要技术手段,然而现有5G宏基站网络能量管理模型主要关注网络通信设备的节能问题,未考虑网络中大量配套设备与通信设备的协调优化。为此,建立5G宏基站网络通信与配套设备协调优化的能量管理模型,所建模型为一混合整数线性优化问题(mixed integer linear programming,MILP)。为处理模型中由于网络用户数和设备数较多所导致的大量0/1变量问题,提出基于地理位置的用户聚类和适应模型的改进Benders算法,以求解大规模5G网络通信与配套设备协调优化模型,并通过算例仿真验证了所提模型和算法的有效性,该模型能适用于多住宅区和大规模商业区的5G宏基站网络能量管理。