Ph.D. student under the direction of Marco Di RENZO

Thesis title: New Contributions to the Modeling of Cellular Networks by Using Stochastic Geometry
Thesis abstract: Experimental activities have shown fundamental limitations of using mmWave frequencies for wireless access: if the transmission distance is greater than 200 m, it is not possible to establish communication links of sufficient high quality for 5G applications. Cellular networks based on small cells are mandatory. To date there is no adequate methodology for optimizing mmWave networks based on small cells. We intend to develop and introduce a new methodological approach for modeling, designing and optimizing multi-tier hyper dense mmWave cellular networks. It relies on the computation and optimization of accurate utility functions, which are obtained with the aid of tools from stochastic geometry, random shape theory and communications theory. Stochastic geometry is used to model the spatial locations of the small cells. Random shape theory is used to incorporate blockages that are essential for a fair assessment of mmWave communications. Communications theory is used for getting utility functions that are of interest for engineering design and optimization. Furthermore, we plan to incorporate for the first time overlaid microwave cells into the mmWave model and predict the performance of such multiband (microwave and mmWave) systems. The spatial correlations originating from spatial blockages will be duly taken into account and new modeling approaches will be developed.