Jingbo Sun

China Telecom Corporation Limited, Peping, Beijing, China

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Publications (5)1.23 Total impact

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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.
    International Journal of Ad Hoc and Ubiquitous Computing 09/2012; 10(4):241-251. DOI:10.1504/IJAHUC.2012.049070 · 0.90 Impact Factor
  • 03/2012; 7(3). DOI:10.4304/jnw.7.3.494-501
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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.
    IEICE Transactions on Communications 02/2012; 95-B(2):591-594. DOI:10.1587/transcom.E95.B.591 · 0.33 Impact Factor
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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.
    Proceedings of the Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2011, Seoul, Korea, June 30-July 02, 2011; 01/2011
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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.
    Proceedings of the 6th International Wireless Communications and Mobile Computing Conference, IWCMC 2010, Caen, France, June 28 - July 2, 2010; 01/2010

Publication Stats

2 Citations
1.23 Total Impact Points


  • 2012
    • China Telecom Corporation Limited
      Peping, Beijing, China
  • 2010–2012
    • Tsinghua University
      • Department of Electronic Engineering
      Peping, Beijing, China