Otimização em redes de backhaul sem fio

Abstract

Technological breakthroughs have transformed the telecommunications industry aiming at providing capacity and efficiency to support the increasing demand for wireless broadband services. With the advances in access technologies, the capacity bottleneck of cellular networks is gradually moving from the radio interface towards the backhaul — the portion of the network infrastructure that provides interconnectivity between the access and core networks. The ability for microwave to be rapidly and cost-effectively deployed is being a crucial point for successfully tackling the backhaul bottleneck problem. However, backhaul solutions available with this technology have received little attention from the scientific community. Nevertheless, the growth of microwave backhaul networks and their increasing complexity give rise to many interesting optimization problems. In fact, unlike wired networks, the capacity of a microwave radio link is prone to variations, either due to external factors (e.g., weather) or by the action of the network operator. This fundamental difference raises a variety of new issues to be addressed appropriately. Therefore, more refined approaches for dealing with network optimization in wireless microwave backhaul need to be conceived. In this thesis, we investigate network optimization problems related to the design and configuration of wireless microwave backhaul. We are concerned with a general class of problems expressed in terms of minimum cost multicommodity flows with discontinuous step increasing cost functions on the links of the network. These problems are among the most important and challenging problems in network optimization. Generally, they are computationally very difficult and, in practice, can only be solved approximately. We introduce mathematical models for some of these problems and present solution approaches essentially based on general mixed integer programming, chance-constrained programming, relaxation techniques, cutting plane methods, as well as hybrid metaheuristics. This work was done in collaboration with the SME 3Roam, and partially developed within the scope of the joint project RAISOM (Réseaux de collecte IP sans til optimisés), among INRIA Sophia Antipolis, SME 3Roam, and SME Avisto. This thesis was developed under joint PhD thesis supervision between the University of Nice-Sophia Antipolis and the Federal University of Ceara".