Mobile data has been growing dramatically in recent years, mainly as a result of the increasing number of mobile devices and the introduction of multimedia services and applications. Due to the rising demand for mobile data and the scarcity of licensed frequency spectrum, telecommunication operators are looking at every tool at hand for solutions to increase the spectral efficiency of the cellular networks. Thanks to the recent advancements in drone technology, it has become viable and cost-effective to quickly deploy small cells in areas of urgent needs by using a drone as a cellular base station. A drone is an unmanned aerial vehicle designed to be flown either through remote control or autonomously using embedded software and sensors, such as GPS.
Historically, drones had been used mainly in military for reconnaissance purposes, but with recent developments in lightweight drones operated with batteries, many civilian applications are emerging. Use of drones to deploy small cells in areas of urgent needs is one of the most interesting applications currently being studied by many researchers. The greatest advantage of this approach is that drones can be fitted with small cell base station (BS) equipment and sent to a specific target location immediately without having to deploy any infrastructure. In the current studies, only the hovering position of the drones in the air is optimized without considering any dynamic repositioning during the service.
The goal of this project is to explore the benefit of dynamic repositioning of the drone during the service in response to the dynamic users activities and mobility. The key idea is to exploit the flying capability and agility of light-weight drones for making the BS continuously chasing the current location of active users within the cell, thereby reducing the distance between BS and UE. By bringing the BS closer to the UE, we can not only reduce the signal attenuation, but also increase the probability of line-of-sight (LoS) for a given altitude of the drone. The combination of these two effects is expected to increase the data rate and hence spectral efficiency of the drone cell. An associated challenge is to ensure that drone energy consumption is not significantly increased due to dynamic repositioning compared to the strict hovering at the same location as considered in previous studies. To this end, we need to design algorithms and evaluate their performances using simulations and experiments.