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A Downlink Coverage Self-optimizing Algorithm for LTE Cellular Networks Based on Big Data Analytics

机译:基于大数据分析的LTE蜂窝网络下行覆盖自优化算法

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摘要

Inappropriate parameters and antenna problems will result in abnormal coverage performance of LTE networks. In order to deal with the problems mentioned above and improve the coverage performance, this paper proposes a downlink coverage Self-optimizing algorithm (DCSA) on the strength of big data analytics. The proposed algorithm obtains and analyzes the data, which records the performance situation of existing wireless networks to locate the cells with abnormal coverage performance. Then a Self-optimizing method is proposed to improve the coverage by adjusting the parameters. In the last part, the analysis results will display that the coverage optimization algorithm is high-efficiency and low-cost for telecom operators.
机译:不适当的参数和天线问题将导致LTE网络的覆盖性能异常。为了解决上述问题并提高覆盖性能,本文提出了一种基于大数据分析的下行链路覆盖自优化算法(DCSA)。该算法获取并分析了数据,记录了现有无线网络的性能状况,以定位覆盖性能异常的小区。然后提出了一种自优化方法,通过调整参数来提高覆盖范围。在最后一部分中,分析结果将表明,覆盖范围优化算法对于电信运营商而言是高效且低成本的。

著录项

  • 来源
  • 会议地点 Chongqing(CN)
  • 作者单位

    Department of Network Optimization and Management, China Unicom Network Technology Research Institute, Beijing 100048, People's Republic of China;

    Department of Network Optimization and Management, China Unicom Network Technology Research Institute, Beijing 100048, People's Republic of China;

    Department of Network Optimization and Management, China Unicom Network Technology Research Institute, Beijing 100048, People's Republic of China;

    Department of Network Optimization and Management, China Unicom Network Technology Research Institute, Beijing 100048, People's Republic of China;

    Department of Network Optimization and Management, China Unicom Network Technology Research Institute, Beijing 100048, People's Republic of China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Big data; Downlink coverage; Data mining; Self-optimizing;

    机译:大数据;下行链路覆盖;数据挖掘;自我优化;

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