  We formulate an optimization problem for maximizing the data rate of a common
message transmitted from nodes within an airborne network broadcast to a
central station receiver while maintaining a set of intra-network rate demands.
Assuming that the network has full-duplex links with multi-beam directional
capability, we obtain a convex multi-commodity flow problem and use a
distributed augmented Lagrangian algorithm to solve for the optimal flows
associated with each beam in the network. For each augmented Lagrangian
iteration, we propose a scaled gradient projection method to minimize the local
Lagrangian function that incorporates the local topology of each node in the
network. Simulation results show fast convergence of the algorithm in
comparison to simple distributed primal dual methods and highlight performance
gains over standard minimum distance-based routing.
