期刊文献+

利用数据挖掘的网络智能感知与自适应优化

Network Self-Optimization and Intelligence Based on Data Mining
在线阅读 下载PDF
导出
摘要 文章提出了一种利用数据挖掘的自适应优化方法。该方法将自优化问题与数据挖掘技术相结合,利用数据挖掘技术对海量数据进行处理,找出表示其中内在规律的知识,利用这些知识进行网络自适应优化。文章以通话业务时长预测分析为例进行分析,结果表明利用数据挖掘进行业务预测的精度高于传统的统计分析方法,论文分析在C-RAN架构下利用数据挖掘对网络状态进行预测是可行的。 In this paper, we propose a self-optimization method based on data mining.With this method, mass data can be processed and laws can be found for self-optimization. We analyze call service prediction and show that using data mining to predict services is more accurate than using statistical methods to predict services We present data mining technology that can be used for network prediction in a C-RAN architecture.
出处 《中兴通讯技术》 2013年第1期35-38,共4页 ZTE Technology Journal
基金 国家科技重大专项(2010ZX03003-008-004)
关键词 自优化 数据挖掘 C—RAN架构网络 基带资源池 self-optimization data mining C-RAN networks baseband resource pool
  • 相关文献

参考文献5

  • 1哈肯 H;徐锡申;陈式刚;陈雅深.协同学,引论:物理学、化学和生物学中的非平衡相变和自组织[M]北京:原子能出版社,1984.
  • 2PREHOFER C,BETTSTETTER C. Self-organization in communication networks:Principles and design paradigms[J].Communications Magazine,2005,(07):78-85.
  • 3张军,张平,田辉.IMT-Advanced系统中的自组织网络技术[J].中兴通讯技术,2011,17(5):1-4. 被引量:3
  • 4朱明.数据挖掘[M]合肥:中国科学技术大学出版社,2002.
  • 5王晓云,黄宇红,崔春风,陈奎林,陈沫.C-RAN:面向绿色的未来无线接入网演进[J].China Communications,2010,7(3):107-112. 被引量:33

二级参考文献14

  • 1Cisco Visual Networking Index[EB/OL]. [2010-6-15]. http ://www.cisco.com/web/go/vni.
  • 2SPENCER Q H, SWINDLEHURST A L, HAARDT M. Zero-forcing Methods for Downlink Spatial Multiplexing in Multiuser MIMO Channels[J]. IEEE Transactions on Signal Processing, 2004, 52(2): 461-471.
  • 3CHOI L U, MURCH R D. A Transmit Preprocessing Technique for Multiuser MIMO Systems using a Decomposition Approach[J]. IEEE Transactions on Wireless Communications, 2004, 3(1): 20-24.
  • 4ZHANG Jun, CHEN Runhua, ANDREWS J G, et al. Coordinated Multi-cell MIMO Systems with Cellula- Block Diagonalization[C]// Proceedings of the 41st Asilomar Conference on Signals, Systems and Computers, 2007: 1669-1673.
  • 5NGMN Recommendation on SQN and Q&M Requirements [S]. 2008.
  • 6FENG Sujuan, SEIDEL E. Self-Organizing Networks{SON) in 3GPP long term evolution [R]. Munich, Germany: Nomor Research GmbH, 2009.
  • 73GPP TR36.300. Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2 [S]. 2010.
  • 83GPP TS32,500. Telecommunication.management; Self-Organizing Networks (SON); Concepts and requirements [S]. 2010.
  • 93GPP TS36.902. Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Self-configuring and Self-Optimizing Network(SON) use cases and solutions [S]. 2010.
  • 103GPP TS32.821. Telecommunication management; Study of Self-Organizing Networks (SON) related operation, administration and maintenance{OAM) for home nodeB(HNB) [S].2010.

共引文献34

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部