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1. 西安电子科技大学综合业务网理论及关键技术国家重点实验室 西安710071
2. 埃塞克斯大学计算机科学与电子工程学院 科尔切斯特 CO4 3SQ
[ "赵国刚,男,西安电子科技大学通信工程学院博士生,主要研究方向为蜂窝网络的高能效基础理论。" ]
[ "赵力强,男,博士,西安电子科技大学综合业务网国家重点实验室博士生导师,主要研究方向为宽带无线接入、绿色无线通信、临近空间通信与异构网络融合等。在国内外学术期刊、国际学术会议上发表相关论文70余篇,其中,SCI检索的论文20余篇、EI检索的论文50余篇,申请国家发明专利5项,主持/参与了国家自然科学基金、国家高技术研究发展计划(“863”计划)、国家科技重大专项等纵向科研课题,欧盟FP6、FP7等国际合作交流项目,华为基金等横向科研项目。" ]
[ "杨鲲,男,博士,英国Essex大学计算机科学和电子工程学院教授,IEEE高级会员,主要研究方向为多种无线网络技术以及这些无线网络和固定网络之间的融合、普适服务工程、网络虚拟化与IP网络管理。已发表超过50篇的国际期刊论文和多部专业书籍以及40多篇国际会议论文,主持了由英国多个科学研究机构(如SPSRC、TSB)、工业界(如英国电信)以及欧盟FP7(如GEYSERS项目)等资助的科研项目。" ]
网络出版日期:2014-07,
纸质出版日期:2014-07-20
移动端阅览
赵国刚, 赵力强, 杨鲲. 面向移动云计算接入网络的高能效无线资源管理[J]. 电信科学, 2014,30(7):53-61.
Guogang Zhao, Liqiang Zhao, Kun Yang. Energy Efficient Radio Resource Allocation in Two-Tier Macro-Femto Cellular for Mobile Cloud Computing[J]. Telecommunications science, 2014, 30(7): 53-61.
赵国刚, 赵力强, 杨鲲. 面向移动云计算接入网络的高能效无线资源管理[J]. 电信科学, 2014,30(7):53-61. DOI: 10.3969/j.issn.1000-0801.2014.07.09.
Guogang Zhao, Liqiang Zhao, Kun Yang. Energy Efficient Radio Resource Allocation in Two-Tier Macro-Femto Cellular for Mobile Cloud Computing[J]. Telecommunications science, 2014, 30(7): 53-61. DOI: 10.3969/j.issn.1000-0801.2014.07.09.
摘要:双层宏蜂窝/小蜂窝异构网络不但能解决室内用户的覆盖问题,还可以大幅度降低网络能量消耗。但是,网络中的跨层和层间干扰会降低网络性能,高能效的无线资源分配和优化方法无疑将成为解决此问题的有效途径。首先,给出了一个移动云计算管理框架。然后,针对无线单链路定义了空间传输效率,比较和分析了多种单链路效率度量的含义和数学性质,并针对基于LTE-A(long term evolution-advanced)的移动云计算接入网络,提出了一种高能效的无线资源管理算法。为了快速地达到最优解,设计了一个快速收敛的迭代算法。仿真分析说明此资源管理算法实现了移动云计算系统能量效率和吞吐量的高效折中。
Two-tier macro-femto-cellular networks have initially been proposed as a solution to the poor indoor coverage problem
but they are also capable of substantially reducing the overall energy consumption. However
the cross-tier and co-tier interference have to be carefully controlled with the aid of specific radio resource allocation and optimization techniques. A mobile cloud computing management architecture was proposed firstly. Then novel concept of spatial transmission efficiency for PtP radio link was first introduced with several existing efficiency metrics compared. An analytical model was conceived and a radio resource management algorithm based on LTE-A mobile cloud computing was designed. In order to achieve the optimal solution quickly
a rapid convergence of the iterative algorithm was designed. Simulation result shows the proposed algorithm achieves the maximum of system energy efficiency with a superior tradeoff with system throughput.
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