Jingbo Sun

China Telecom Corporation Limited, Peping, Beijing, China

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Publications (5)0.78 Total impact

  • Source
    Jingbo Sun · Hongbo Si · Yue Wang · Jian Yuan · Xiuming Shan · Ilsun You
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    ABSTRACT: Aggregate mobility modelling, studying macroscopic rule of human movement, benefits the performance of mobility management. This paper is primarily focused on establishing an architecture based on field theory, using scalar and vector field to describe traffic and mobility, respectively. On the basis of their temporal-spatial evolution, we try to discover the relationship between traffic field and mobility field. This field architecture fits for mobility management in large temporal-spatial scale, since it not only benefits qualitative analysis of traffic and mobility in the perspective of field, but also provides a theoretical foundation and insight for issues in mobile communication.
    Full-text · Article · Sep 2012 · International Journal of Ad Hoc and Ubiquitous Computing
  • Source
    Hongzeng He · Jingbo Sun · Yue Wang · Qi Liu · Jian Yuan
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    ABSTRACT: Recent studies on green communications and networks indicate that most traffic loads could be served by a certain part of base stations during the low load period. In this paper, we present an energy saving approach which is based on the cluster analysis of traffic loads in urban space. Consequently, different traffic patterns are discovered and specific switching-off approaches are applied to the different traffic patterns. Simulation results reveal that a better energy saving performance can be attained compared to the existing approach.
    Preview · Article · Mar 2012 · Journal of Networks
  • Jingbo Sun · Yue Wang · Jian Yuan · Xiuming Shan
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    ABSTRACT: Since most of energy consumed by the telecommunication infrastructure is due to the Base Transceiver Station (BTS), switching off BTSs when traffic load is low has been recognized as an effective way of saving energy. In this letter, an energy saving scheme is proposed to minimize the number of active BTSs based on the space-time structure of traffic loads as determined by principal component analysis. Compared to existing methods, our approach models traffic loads more accurately, and has a much smaller input size. As it is implemented in an off-line manner, our scheme also avoids excessive communications and computing overheads. Simulation results show that the proposed method has a comparable performance in energy savings.
    No preview · Article · Feb 2012 · IEICE Transactions on Communications
  • Jingbo Sun · Yue Wang · Jian Yuan · Xiuming Shan
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    ABSTRACT: In cellular networks, accurate predictions of loca- tion update and paging are essential to attain reliable results of location area planning. In this paper, a novel approach using principal component analysis is proposed to model location update and paging, revealing the low intrinsic dimensionality. Compared with existing methods, the proposed approach not only makes predictions adaptively, but also provides higher temporal resolution. These are valuable for dynamically adapt- ing LAs to variation of location update and paging. The analysis is based on original data from a real cellular network.
    No preview · Conference Paper · Jan 2011
  • Jingbo Sun · Yue Wang · Hongbo Si · Xia Mao · Jian Yuan · Xiuming Shan
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    ABSTRACT: Understanding of urban mobility dynamics benefits both aggregate human mobility in wireless communications, and the planning and provision of urban facilities and services. Due to the high penetration of cell phones, the cellular networks provide information for urban dynamics with large spatial extent and continuous temporal coverage. In this paper, a novel approach is proposed to explore the space-time structure of urban dynamics, based on the original data collected by cellular networks in a southern city of China, recording population distribution by dividing the city into thousands of pixels. By applying principal component analysis, the intrinsic dimensionality is revealed. The structure of all the pixel population variations could be well captured by a small set of eigen pixel population variations. According to the classification of eigen pixel population variations, each pixel population variation can be decomposed into three constitutions: deterministic trends, short-lived spikes, and noise. Moreover, the most significant eigen pixel population variations are utilized in the applications of forecasting and anomaly detection.
    No preview · Conference Paper · Jan 2010