Modeling Mobile Cellular Networks Based on Social Characteristics

  • Ji Ma Beijing University of Posts and Telecommunications
  • Wei Ni Digital Productivity Flagship, CSIRO, Australia, 2122
  • Jie Yin Digital Productivity Flagship, CSIRO, Australia, 2122
  • Ren Ping Liu Digital Productivity Flagship, CSIRO, Australia, 2122
  • Yuyu Yuan Beijing University of Posts and Telecommunications Beijing, China, 100876
  • Binxing Fang Beijing University of Posts and Telecommunications Beijing, China, 100876

Abstract

Social characteristics have become an important aspect of cellular systems, particularly in next generation networks where cells are miniaturised and social effects can have considerable impacts on network operations. Traffic load demonstrates strong spatial and temporal fluctuations caused by users social activities. In this article, we introduce a new modelling method which integrates the social aspects of individual cells in modelling cellular networks. In the new method, entropy based social characteristics and time sequences of traffic fluctuations are defined as key measures, and jointly evaluated. Spectral clustering techniques can be extended and applied to categorise cells based on these key parameters. Based on the social characteristics respectively, we implement multi-dimensional clustering technologies, and categorize the base stations. Experimental studies are carried out to validate our proposed model, and the effectiveness of the model is confirmed through the consistency between measurements and model. In practice, our modelling method can be used for network planning and parameter dimensioning to facilitate cellular network design, deployments and operations.

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Published
2016-07-03
How to Cite
MA, Ji et al. Modeling Mobile Cellular Networks Based on Social Characteristics. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 11, n. 4, p. 480-492, july 2016. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/2054>. Date accessed: 04 july 2020. doi: https://doi.org/10.15837/ijccc.2016.4.2054.

Keywords

social characteristics, mobile networks, spectral clustering, energy efficiency, traffic model