  Resource reservation is an essential step to enable wireless data networks to
support a wide range of user demands. In this paper, we consider the problem of
joint resource reservation in the backhaul and Radio Access Network (RAN) based
on the statistics of user demands and channel states, and also network
availability. The goal is to maximize the sum of expected traffic flow rates,
subject to link and access point budget constraints, while minimizing the
expected outage of downlinks. The formulated problem turns out to be non-convex
and difficult to solve to global optimality. We propose an efficient Block
Coordinate Descent (BCD) algorithm to approximately solve the problem. The
proposed BCD algorithm optimizes the link capacity reservation in the backhaul
using a novel multipath routing algorithm that decomposes the problem down to
link-level and parallelizes the computation across backhaul links, while the
reservation of transmission resources in RAN is carried out via a novel
scalable and distributed algorithm based on Block Successive Upper-bound
Minimization (BSUM). We prove that the proposed BCD algorithm converges to a
Karush-Kuhn-Tucker solution. Simulation results verify the efficiency and the
efficacy of our BCD approach against two heuristic algorithms.
