Stochastic geometry-based analysis of wireless communication networks

The objective of this master thesis is to develop an innovative framework enabling to model wireless networks and to assess their performance. This framework includes on the one hand Monte Carlo simulations and on the other hand analytical expressions derived thanks to the stochastic geometry theory. The result of this work aims at providing an optimization tool applicable to modern and future networks (e.g. relying on the 5G technology). We hence focus on three aspects that are considered to be crucial for such networks : the modeling of the propagation environment, the beamforming and the transmit power monitoring. Each of these topics is analyzed in order to gain insight into their impact on the global performance. Then, a heterogeneous network encompassing these three aspects is proposed.