“Density-Adaptive Mobile Networks” by Shahram Mollahasani

We experience a major paradigm change in mobile networks. The infrastructure of the network becomes mobile as it is densified by using mobile and nomadic small cells to increase coverage and capacity. Furthermore, the innovative approaches such as green operation through sleep scheduling, user-controlled base stations, and slicing will make the network highly dynamic. Small cells, while bringing many benefits, introduce unconventional challenges. We have to introduce novel techniques for adapting the communications stacks to the context of the network in terms of the density while considering dense and sparse networks conjointly. Especially when mobile base stations such as drone cells are considered, static and man-made configurations will waste valuable resources such as spectrum or energy if density is not considered as an optimization parameter. In this work, we will qualitatively analyze the impact of density on network performance, and present an analytic model to obtain insight as to how the capacity of a network changes as it becomes denser. We will also work on implementation of density-adaptive energy-efficient algorithms for stationary, nomadic and user-controlled base stations by obtaining the optimum value of UEs, antennas and base stations in our scenarios.