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Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

机译:了解城市环境中大型蜂窝塔的移动交通模式

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摘要

Understanding mobile traffic patterns of large scale cellular towers in urban environment is extremely valuable for Internet service providers, mobile users, and government managers of modern metropolis. This paper aims at extracting and modeling the traffic patterns of large scale towers deployed in a metropolitan city. To achieve this goal, we need to address several challenges, including lack of appropriate tools for processing large scale traffic measurement data, unknown traffic patterns, as well as handling complicated factors of urban ecology and human behaviors that affect traffic patterns. Our core contribution is a powerful model which combines three dimensional information (time, locations of towers, and traffic frequency spectrum) to extract and model the traffic patterns of thousands of cellular towers. Our empirical analysis reveals the following important observations. First, only five basic time-domain traffic patterns exist among the 9600 cellular towers. Second, each of the extracted traffic pattern maps to one type of geographical locations related to urban ecology, including residential area, business district, transport, entertainment, and comprehensive area. Third, our frequency-domain traffic spectrum analysis suggests that the traffic of any tower among 9600 can be constructed using a linear combination of four primary components corresponding to human activity behaviors. We believe that the proposed traffic patterns extraction and modeling methodology, combined with the empirical analysis on the mobile traffic, pave the way toward a deep understanding of the traffic patterns of large scale cellular towers in modern metropolis.
机译:对于城市服务的Internet服务提供商,移动用户和政府管理人员而言,了解城市环境中大型蜂窝塔的移动流量模式极为重要。本文旨在提取和建模部署在大城市中的大型塔的交通模式。为了实现这一目标,我们需要解决几个挑战,包括缺乏处理大型交通测量数据的适当工具,未知的交通模式以及处理影响交通模式的复杂城市生态因素和人类行为。我们的核心贡献是强大的模型,该模型结合了三维信息(时间,塔的位置和交通频谱),以提取和建模数千个蜂窝塔的交通模式。我们的经验分析揭示了以下重要观察结果。首先,在9600个蜂窝塔之间仅存在五个基本的时域流量模式。其次,每个提取的交通模式都映射到与城市生态相关的一种地理位置,包括居民区,商业区,交通,娱乐和综合区。第三,我们的频域交通频谱分析表明,可以使用对应于人类活动行为的四个主要成分的线性组合来构建9600中任何一座塔的交通。我们认为,所提出的交通模式提取和建模方法,结合对移动交通的实证分析,为深入理解现代都市中大型蜂窝塔的交通模式铺平了道路。

著录项

  • 来源
    《IEEE/ACM Transactions on Networking》 |2017年第2期|1147-1161|共15页
  • 作者单位

    Department of Electronic Engineering, State Key Laboratory on Microwave and Digital Communications and the Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

    Department of Electronic Engineering, State Key Laboratory on Microwave and Digital Communications and the Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

    Department of Electronic Engineering, State Key Laboratory on Microwave and Digital Communications and the Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

    Department of Electrical Engineering and Computer Science, Stanford University, Stanford, CA, USA;

    Department of Electronic Engineering, State Key Laboratory on Microwave and Digital Communications and the Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

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

    Poles and towers; Mobile communication; Urban areas; Base stations; Ecology; Biological system modeling; Data visualization;

    机译:杆塔;移动通信;城市地区;基站;生态学;生物系统建模;数据可视化;

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