超密集网中一种基于人工蜂群的节能分簇算法

周朋光; 黄俊伟; 张仁迟; 徐浩

doi:10.11959/j.issn.1000-0801.2017038

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超密集网中一种基于人工蜂群的节能分簇算法

研究与开发 | 更新时间：2024-06-05

- 超密集网中一种基于人工蜂群的节能分簇算法
- An energy saving clustering algorithm based on artificial bee colony in ultra dense network
- 电信科学 2017年33卷第2期页码：90-97
- 作者机构：
- 作者简介：
  
  [ "周朋光（1992-），男，重庆邮电大学硕士生，主要研究方向为5G关键技术、超密集网络中的干扰协调技术。" ]
  [ "黄俊伟（1969-），男，重庆邮电大学高级工程师、硕士生导师，主要研究方向为新一代宽带移动通信核心芯片、协议及系统应用、宽带无线通信。" ]
  [ "张仁迟（1991-），男，重庆邮电大学硕士生，主要研究方向为LTE/5G相关关键技术。" ]
  [ "徐浩（1992-），男，重庆邮电大学硕士生，主要研究方向为5G 关键技术、毫米波MIMO系统混合波束成形技术。" ]
- 基金信息：
  
  国家科技重大专项基金资助项目;The National Science and Technology Major Project of China(2016ZX03002010-003)
- DOI：10.11959/j.issn.1000-0801.2017038
  中图分类号： TN929.5
- 网络出版日期：2017-02，
  
  纸质出版日期：2017-02-20
- 稿件说明：
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周朋光, 黄俊伟, 张仁迟, 等. 超密集网中一种基于人工蜂群的节能分簇算法[J]. 电信科学, 2017,33(2):90-97.

Pengguang ZHOU, Junwei HUANG, Renchi ZHANG, et al. An energy saving clustering algorithm based on artificial bee colony in ultra dense network[J]. Telecommunications science, 2017, 33(2): 90-97.
周朋光, 黄俊伟, 张仁迟, 等. 超密集网中一种基于人工蜂群的节能分簇算法[J]. 电信科学, 2017,33(2):90-97. DOI： 10.11959/j.issn.1000-0801.2017038.

Pengguang ZHOU, Junwei HUANG, Renchi ZHANG, et al. An energy saving clustering algorithm based on artificial bee colony in ultra dense network[J]. Telecommunications science, 2017, 33(2): 90-97. DOI： 10.11959/j.issn.1000-0801.2017038.

摘要

超密集网络中，密集部署的低功率基站将会加大系统的能耗，并且造成紧缺频谱资源的浪费。探寻干扰协调和系统节能的可行性方法在超密集网络架构下提出基站的休眠—唤醒—活跃机制，减小了休眠基站直接转为活跃状态的开启时间；另外，提出一种基于人工蜂群染色分簇算法，尽可能使用最少的颜色给拓扑图中的小区染色，并对簇内活跃基站进行优化功率分配。经仿真表明，休眠—唤醒—活跃机制能够提升系统的能源效率，染色分簇算法也可以改善用户的频谱效率和吞吐量。

Abstract

In ultra dense network (UDN)

the dense deployment of low power base station (BS) will increase the system's energy consumption and cause the waste of the scarce spectrum resources.Aiming to explore the feasible method of energy saving system and interference coordination

BS sleeping-waking-active mechanism in UDN was proposed

which would reduce the opening time of the sleeping BS.Also an adjusted artificial bee colony algorithm was proposed which used the least colors to dye the BS in topology

then power allocation of active BS in different cluster was optimized.Simulations show that the sleeping-waking-active mechanism can improve the energy efficiency of the system

and the clustering algorithm can promote the spectrum efficiency and throughput.

关键词

Keywords

references

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