计算机应用 ›› 2015, Vol. 35 ›› Issue (6): 1505-1508.DOI: 10.11772/j.issn.1001-9081.2015.06.1505

• 网络与通信 •    下一篇

基于能效的异构无线网络联合切换调度和资源分配算法

邱畅啸, 冷甦鹏, 叶宇   

  1. 电子科技大学 通信与信息工程学院, 成都 611731
  • 收稿日期:2015-01-04 修回日期:2015-03-20 出版日期:2015-06-10 发布日期:2015-06-12
  • 通讯作者: 冷甦鹏(1973-),男,四川攀枝花人,教授,博士生导师,博士,主要研究方向:无线宽带与移动通信网络、物联网、智能交通;spleng@uestc.edu.cn
  • 作者简介:邱畅啸(1990-),男,湖北黄冈人,硕士研究生,主要研究方向:无线网络资源管理;叶宇(1988-),男,重庆人,硕士研究生,主要研究方向:无线网络资源管理。
  • 基金资助:

    国家科技支撑计划项目(2011BAK12B02);国家科技重大专项(2014ZX03004-02);国家863计划项目(2012AA011402);中央高校基本科研业务费专项资金资助项目(ZYGX2013J009);新世纪优秀人才支持计划项目(NCET-10-0294)。

Joint switch scheduling and resource allocation algorithm based on energy efficiency in heterogeneous wireless networks

QIU Changxiao, LENG Supeng, YE Yu   

  1. School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China
  • Received:2015-01-04 Revised:2015-03-20 Online:2015-06-10 Published:2015-06-12

摘要:

在宏蜂窝和微蜂窝并存的异构无线网络中,为了提高系统能效,提出了一种联合切换调度和资源分配(JSRA)算法。首先,利用基于微基站睡眠的集中式切换调度算法(CUSA)来确定用户的关联基站,CUSA将微基站用户全部切换到宏基站是否能减少功耗作为判断微基站睡眠的准则;然后,基站采用基于最优信道质量的子载波分配调整(BCSA)算法为用户分配子载波和传输功率,BCSA算法通过调整最大能效用户和最小能效用户之间的子载波分配,保证网络能效逼近最优解。理论分析和实验仿真表明,同单独考虑用户切换或资源分配的三种算法相比,JSRA算法复杂度偏高,但是在用户数为120时网络功耗最多降低44.4%,用户总速率只比一种对比算法略有下降,最多提升80%,网络能效最多提升200%。实验结果表明,JSRA算法能够有效提高异构无线网络的网络能效。

关键词: 异构无线网络, 能效, 用户切换, 资源分配, 子载波

Abstract:

In order to improve the energy efficiency of the heterogeneous wireless networks with macro-cells and micro-cells, a Joint Switch scheduling and Resource Allocation (JSRA) algorithm was proposed. Firstly, based on sleeping of micro base stations, Centralized User Switch scheduling Algorithm (CUSA) was adopted to determine the associated base station for each user. The sleeping/waking status of a micro base station was judged according to whether to decrease of network power consumption when users of the micro base station entirely switched to macro base station.Then, the Best Channel quality Subcarrier Adjustment (BCSA) algorithm was used to assign subcarriers and transmission power for users. The network energy efficiency was guaranteed to approximate the optimal solution by adjusting the subcarrier allocation between the user with the maximum energy efficiency and the user with the minimum energy efficiency. The theoretical analysis and simulation experiments show that,compared with three existing algorithms which considered user handoff or resource allocation separately, JSRA has high computational complexity; however, when the number of users is 120, JSRA can reduce network power consumption 44.4% at most, increase the total effective data rate of users by 80% with the slight reduction only than one contrast as well as the energy efficiency of the network by 200% at most. Experimental results show JSRA can improve the energy efficiency of heterogeneous wireless networks effectively.

Key words: heterogeneous wireless network, energy efficiency, user handoff, resource allocation, subcarrier

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