Figure 1

Schematic of the algorithm. Graphical representation of the proposed approach. The physical network is a collection of terminals (gray circles) connected by wireless links: data (solid lines) and interference (dashed lines) links. The state of the terminals is defined by a collection of variables whose value evolves over time. The temporal evolution of the state of the terminals and of the links is modeled by the logical graph of the network. A sample-path of the network on the logical graph generates a sequence of observations, that are used to estimate the transition matrix$\widehat{\mathbf{P}}\left(t\right)$ and the cost vector$\widehat{\mathbf{c}}\left(t\right)$. The cost function is projected onto a diffusion wavelet basis. A concise representation in the wavelet domain of the long-term cost function$\overline{\mathbf{c}}$ is found as the solution of a sparse approximation problem.