Ultra-Dense Mobile Networks: Optimal Design and Communications Strategies

This thesis conducts an extensive analysis within the mobile telecommunications sub-field of the ultra-dense mobile networks, in which a massive deployment of network’s pieces of equipment is assumed. Future cache-enabled mobile networks are expected to meet most of the generated content demands directly at the edge, where each node has the availability to proactively store a set of contents in a local memory. This thesis makes several important contributions. The research being presented in this thesis proposes new analytical expressions to modeling the performance associated to the network’s edge. Base-stations’ idling technologies are also investigated to temporarily turn off some network nodes, saving energy and, in some circumstances, improving the overall performance by contributing less interference at the network’s edge. On the other hand, making use of fewer base-stations however reduces the amount of available resources at the network’s edge. A trade-off is investigated, which balances among interference saturation and available resources to increase the average user’s quality of experience. In this work, we treat the edge node density as a variable of the problem. This greatly increases the difficulty of obtaining analytical expressions, but also offers a direct access for optimizing the users’ average performance and network’s energy consumptions. An energy-focused performance metric is subsequently proposed, with the intention to highlight an interesting duality within the same network’s tier, which can transition from a better efficient to a more performing state, according to the energy expenses from the operators. Nonetheless, under an ultra-dense scenario, line-of-sight wireless links between the user and the nodes become more likely. The introduction of a main component of the multi-path propagated copies of a signal involves analytical complications. A feasible approximation is proposed and validated through a set of computer simulations. The scalability of the proposed technique allows to generalise existing results in the literature