Stochastic geometric analysis of energy efficiency in two-tier heterogeneous networks

The exponential growth in the number of users of cellular mobile networks (and their requirements) has created a massive challenge for network operators to cope with demands for coverage and data rates. Among the possible solutions for the ever increasing user needs, the deployment of Heterogeneous Networks (HetNets) constitutes both a practical and an economical solution. Moreover, while the typical approach for network
operators has been to consider the coverage and data rates as design parameters in a network, a major concern for next generation networks is the efficiency in the power usage of the network. Therefore, in recent years
the energy efficiency parameter has gathered a great deal of attention in the design of next generation networks.

In the context of HetNets, while the densification of the network in terms of the number of base stations deployed can potentially increase the coverage and boost the data rates, it can also lead to a huge power consumption as the energy used escalates with the number of base stations deployed. To this end, the purpose of this thesis is to investigate the energy efficiency performance of different deployment strategies in a HetNet consisting of macro- and femtocells. We make use of well established tools from stochastic geometry to model the different strategies, as it provides a
theoretical framework from which the scalability of the network in terms of the design parameters can be taken into account. Those strategies consisted first, on the analysis of the effect of using multiple antennas and
diversity schemes on both, the throughput and the energy efficiency of the network. The optimum diversity schemes and antenna configurations were found for an optimal energy efficiency while keeping constraints on
the quality of Service of both tiers. Then, the effect of the vertical antenna tilt was analyzed for both, a traditional macrocell only network and a two-tier network. The optimum antenna tilt in terms of energy efficiency was found while keeping constraints on the Quality of Service required. Finally, an energy efficient deployment of femtocells was proposed where the smart positioning of femtocells derived into improvements of coverage probability, effective throughput and energy efficiency of the network. The proposed model also improved in general the performance of the cell
edge user which in turn resulted in a more balanced network in terms of the overall performance.