In this paper, an analysis of 3G network user data traffic is presented. With the increasing demands for high data rate and energy-efficient cellular service, it is important to understand how cellular user data traffic changes over time and in space. We provide statistical modelling of timevarying throughput per cell and the distribution of instantaneous throughput per cell over different cells based on throughput measurements from a real-world large-scale urban cellular network. Based on our inspection of the large set of cellular data traffic measurements, user data traffics on weekday and weekend are analyzed separately. Our proposed statistical models can generate network traffic data that are very close to the measured traffic and can be used in simulations of large-scale urban-area mobile networks.

Abstract-As the mobile data demand keeps growing, an existing heterogeneous network (HetNet) composed of macrocells and small cells may still face the problem of not being able to provide sufficient capacity for unexpected but reoccurring hot spots. In this paper, we propose a mobile small-cell deployment strategy that avoids replanning the overall network while fulfilling the hot spot demand by optimizing the deployment of additional mobile small cells on top of the existing HetNet. We formulate the problem as a joint optimization over the number and locations of mobile small cells and the user associations of all cells in order to maximize the minimum user throughput. In order to solve it, we first propose a Fixed Number Deployment Algorithm (FNDA) to solve the problem with a fixed number of new small cells. Afterwards, we extend FNDA into a Deployment Over Existing Network Algorithm (DOENA) to solve the joint optimization problem. The simulation results show that DOENA offers a higher minimum user throughput while requiring less mobile small cells to be deployed than the deployment optimization based on maximizing sum user throughput.

Hot spots (HSs) of mobile users that were not expected in the original network planning may occur after a heterogeneous network (HetNet) has been deployed and affect the network performance. In this case, deploying additional small cells on top of the existing HetNet without changing the existing network infrastructure is considered as a solution. In this paper, we first provide a stochastic geometry analysis for a HetNet affected by a large HS and for the additional small cells that need to be deployed based on the spatial bivariate Poisson point process. The optimal numbers of additional small cells required in the HS and non-HS areas are obtained by minimizing the difference between the numbers of macrocell users after and before the HS occurs based on the analytical results. We then propose an algorithm to maximize the average user throughput by jointly optimizing the locations of additional small cells and user associations of all cells. Simulation results show that the proposed algorithm can maintain the average user throughput above a threshold with excellent fairness among all users even for a very high density of HS users.