Energy Efficient Radio Resource Allocation in Two-Tier Macro-Femto Cellular for Mobile Cloud Computing

Guogang Zhao; Liqiang Zhao; Kun Yang

doi:10.3969/j.issn.1000-0801.2014.07.09

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Energy Efficient Radio Resource Allocation in Two-Tier Macro-Femto Cellular for Mobile Cloud Computing

Research and development | 更新时间：2024-06-05

- Energy Efficient Radio Resource Allocation in Two-Tier Macro-Femto Cellular for Mobile Cloud Computing
- Telecommunications Science Vol. 30, Issue 7, Pages: 53-61(2014)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1000-0801.2014.07.09
  CLC：
- Published Online：2014-07，
  
  Published：20 July 2014
- 稿件说明：
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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：

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

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。

Abstract

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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references

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