Dynamic network configuration: Hotspot identification for Virtual Small Cells

摘要

One of the envisaged candidates technologies to be used in next generation mobile networks is the integration of a large number of antennas at the Base Station (BS), known as Massive Multiple-Input Multiple-Output (MIMO). Massive MIMO can focus the energy on a user or group of users to improve their throughput and the network capacity. An approach of this technology focuses on the creation of coverage areas with the size of a pico-cell, called Virtual Small Cells (VSCs). Their main advantage is that they allow increasing the network capacity while avoiding the deployment cost of new small BSs. Identifying the dense traffic areas in real time and serving them in a responsive way is a key challenge to be address. Our work focuses on dynamically identifying the dense traffic areas so that the VSCs can be implemented and adjust their coverage. To conduct this research we use the K-means method and propose an algorithm that dynamically determines the hotspot parameters for VSCs, i.e., center and radius in order to optimize the overall capacity of the mobile network. Note that this algorithm could be used to identify any group of users.