Ph.D. student under the direction of M. Direnzo

Thesis title: Modeling and Analysis of Ultra-Dense Heterogeneous Cellular Networks by Using Stochastic Geometry
Thesis abstract: Stochastic geometry is one of the most promising solutions to evaluate large-scale system performance of next cellular networks (5G) which are heterogeneous networks. The advantages of stochastic geometry approach not only take into account the randomness of network topology but also provide a powerful mathematical and statistical tool for modeling, analysis system performance of next cellular networks. As a consequence, in this thesis, based on the stochastic geometry approach, I firstly study a realistic modeling of next generation cellular networks. Next, based on the proposed modeling, I develop a new mathematical methodologies for evaluating performance, spectral and energy efficiency of super-dense multi-tier heterogeneous cellular networks.

Stochastic geometry is one of the most promising solutions to evaluate large-scale system performance of next cellular networks (5G) which are heterogeneous networks. The advantages of stochastic geometry approach not only take into account the randomness of network topology but also provide a powerful mathematical and statistical tool for modeling, analysis system performance of next cellular networks. As a consequence, in this thesis, based on the stochastic geometry approach, I firstly study a realistic modeling of next generation cellular networks. Next, based on the proposed modeling, I develop a new mathematical methodologies for evaluating performance, spectral and energy efficiency of super-dense multi-tier heterogeneous cellular networks.