针对密集macro-femto融合网络,提出一种基于长期稳定的切换(long-term-based handover,LTBH)决策算法.该算法由切换角(angle of handover,AHO)和逗留时间(time-to-stay,TTS)2种参数联合进行切换判决,从而有效减小冗余切换次数.首先,在...针对密集macro-femto融合网络,提出一种基于长期稳定的切换(long-term-based handover,LTBH)决策算法.该算法由切换角(angle of handover,AHO)和逗留时间(time-to-stay,TTS)2种参数联合进行切换判决,从而有效减小冗余切换次数.首先,在大量候选基站(candidate base stations,CBSs)场景中提出了AHO参数,从而降低算法的计算复杂度.其次,针对固定基站和移动基站2种基站模型,分别提出了2种TTS参数用于切换用户的切换决策.仿真结果显示,所提的LTBH算法能够在密集macro-femto网络中保证移动用户一定传输速率的基础上有效地降低网络中的切换次数.展开更多
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The National Natural Science Foundation of China(No.61471164)the Fundamental Research Funds for the Central Universitiesthe Scientific Innovation Research of College Graduates in Jiangsu Province(No.KYLX-0133)
文摘针对密集macro-femto融合网络,提出一种基于长期稳定的切换(long-term-based handover,LTBH)决策算法.该算法由切换角(angle of handover,AHO)和逗留时间(time-to-stay,TTS)2种参数联合进行切换判决,从而有效减小冗余切换次数.首先,在大量候选基站(candidate base stations,CBSs)场景中提出了AHO参数,从而降低算法的计算复杂度.其次,针对固定基站和移动基站2种基站模型,分别提出了2种TTS参数用于切换用户的切换决策.仿真结果显示,所提的LTBH算法能够在密集macro-femto网络中保证移动用户一定传输速率的基础上有效地降低网络中的切换次数.
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.
