...
首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >IMPSO and Linear Programming-Based Energy-Efficient Cell Association Algorithm for Backhaul-Constrained Ultra-Dense Small-Cell Networks
【24h】

IMPSO and Linear Programming-Based Energy-Efficient Cell Association Algorithm for Backhaul-Constrained Ultra-Dense Small-Cell Networks

机译:IMPSO and Linear Programming-Based Energy-Efficient Cell Association Algorithm for Backhaul-Constrained Ultra-Dense Small-Cell Networks

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

This paper studies the energy efficiency optimization problem for coordinated multipoint (CoMP)-enabled and backhaul-constrained ultra-dense small-cell networks (UDNs). Energy efficiency is an eternal topic for future wireless communication networks; however, taking actual bottleneck of the backhaul link and the coordinated network architecture into consideration, it is difficult to find an effective way to improve the energy efficiency of the network. Aiming at this problem, we propose to combine cell association, subchannel allocation, backhaul resource allocation, and sleep/on of the cells together to develop an optimization algorithm for energy efficiency in UDN and then solve the formulated energy efficiency optimization problem by means of improved modified particle swarm optimization (IMPSO) and linear programming in mathematics. Simulation results indicate that nearly 13% energy cost saving and 21% energy efficiency improvement can be obtained by combining IMPSO with linear programming, and the backhaul link data rate can be improved by 30% as the number of small cells increases. From the results, it can be found that by combining IMPSO with linear programming, the proposed algorithm can improve the network energy efficiency effectively at the expense of limited complexity.

著录项

  • 来源
  • 作者单位

    Chongqing Univ Posts & Telecommun, Key Lab Ind Internet Things & Networked Control, Minist Educ, Chongqing 400065, Peoples R China|Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Jiangsu, Peoples R China;

    Nanjing Xiaozhuang Univ, Sch Elect & Engn, Nanjing 211171, Peoples R China|Jiangsu Key Construct Lab IoT Applicat Technol, Wuxi, Jiangsu, Peoples R China;

    Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R ChinaNanjing Xiaozhuang Univ, Sch Elect & Engn, Nanjing 211171, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 英语
  • 中图分类
  • 关键词

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号