计算机工程 ›› 2019, Vol. 45 ›› Issue (2): 92-100.doi: 10.19678/j.issn.1000-3428.0049254

• 移动互联与通信技术 • 上一篇    下一篇

基于众包感知的移动网络小区信息侦测方法

李克a,王海a,徐小龙a,杜煜b   

  1. 北京联合大学 a.智慧城市学院; b.机器人学院,北京 100101
  • 收稿日期:2017-11-10 出版日期:2019-02-15 发布日期:2019-02-15
  • 作者简介:李克(1972—),男,教授、博士,主研方向为网络测量与评价、移动互联网业务分析、数据挖掘;王海、徐小龙,硕士研究生;杜煜,教授、博士。
  • 基金项目:

    国家自然科学基金(61372088);北京市科技计划课题(D161100003516003);北京市朝阳区协同创新项目(cyxc1815);北京联合大学人才强校优选计划(BPRH2018cz05)。

Mobile Network Cell Information Detection Method Based on Mobile Crowdsensing

LI Ke a,WANG Hai a,XU Xiaolong a,DU Yu b   

  1. a.College of Smart City; b.College of Robotics,Beijing Union University,Beijing 100101,China
  • Received:2017-11-10 Online:2019-02-15 Published:2019-02-15

摘要:

基站信息表是电信运营商进行移动网络运营和维护的核心数据资产,对于位置服务提供商具有重要的商业价值,但其存在基站信息更新不及时、不准确、第三方无法获取等问题,限制了基站信息表的应用范围和效果。针对该问题,提出一种基于移动众包感知数据的移动网络小区信息侦测方法。借助于众包感知的方式从海量普通用户智能终端上采集用户真实在网信息,利用数据挖掘算法对各基站小区关键参数进行估算,从而构建能够反映网络真实状态的基站信息表。基于现网真实数据的计算结果表明,与现有移动网络小区信息侦测方法相比,该方法具有更高的准确性和较强的信息侦测能力。

关键词: 移动众包感知, 基站信息表, 基于位置服务, 数据挖掘, 网络测量

Abstract:

The base station information table is the core data asset for the telecom operator to operate and maintain the mobile network.It has important commercial value for the location service provider,but there are problems that the base station information update is not timely,inaccurate,and the third party cannot obtain it these,limit the application range and effect of the base station information table.Aiming at these problems,a mobile network cell information detection method based on Mobile Crowdsensing(MCS) perception data is proposed.By means of crowdsourcing perception,the user’s real network information is collected from the mass ordinary user intelligent terminal,and the data mining algorithm is used to estimate the key parameters of each base station cell,thereby constructing a base station information table that can reflect the real state of the network.Calculation results based on the real data of network show that the method has higher accuracy and richer information detection capability than the existing methods.

Key words: Mobile Crowdsensing(MCS) perception, base station information table, Location Based Service(LBS), data mining, network measurement

中图分类号: