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Leveraging diversity to optimize performance in mobile networks

To cope with the rapid increase in mobile data traffic volume, mobile network operators can leverage the diversity in traffic patterns to improve network performance. In this paper, we show how can mobile network operators leverage diversity across different devices and geographical regions to improve traffic models and radio resource allocation, respectively. We conduct trace-driven simulations using data sets collected from an operational mobile network to evaluate our proposed approaches. Our experimental results indicate that diversity-aware traffic model refinements can improve the accuracy of traffic models and radio resource allocation.