Optimization of capacity and energy consumption of wireless mesh network ; Optimisation de la capacité et de la consommation énergétique dans les réseaux maillés sans fil

Wireless mesh networks (WMN) are a promising solution to support high data rate and increase the capacity provided to users, e.g. for meeting the requirements of mobile multimedia applications. However, the rapid growth of traffic load generated by the terminals is accompanied by an unsustainable increase of energy consumption, which becomes a hot societal and economical challenges. This thesis relates to the problem of the optimization of network capacity and energy consumption of wireless mesh networks. The network capacity is defined as the maximum achievable total traffic in the network per unit time. This thesis is divided into four main parts. First, we address the problem of improvement of the capacity of 802.11 wireless mesh networks. We highlight some insensible properties and deterministic factors of the capacity, while it is directly related to a bottleneck problem. Then, we propose a joint TDMA/CSMA scheduling strategy for solving the bottleneck issue in the network. Second, we focus on broadband wireless mesh networks based on time-frequency resource management. In order to get theoretical bounds on the network performances, we formulate optimization models based on linear programming and column generation algorithm. These models lead to compute an optimal offline configuration which maximizes the network capacity with low energy consumption. A realistic SINR model of the physical layer allows the nodes to perform continuous power control and use a discrete set of data rates. Third, we use the optimization models to provide practical engineering insights on WMN. We briefly study the tradeoff between network capacity and energy consumption using a realistic physical layer and SINR interference model. Finally, we focus on capacity and energy optimization for heterogeneous cellular networks. We develop, first, optimization tools to calculate an optimal configuration of the network that maximizes the network capacity with low energy consumption. We second propose a heuristic algorithm that calculates a ...