  We consider a broad class of interference coordination and resource
allocation problems for wireless links where the goal is to maximize the sum of
functions of individual link rates. Such problems arise in the context of, for
example, fractional frequency reuse (FFR) for macro-cellular networks and
dynamic interference management in femtocells. The resulting optimization
problems are typically hard to solve optimally even using centralized
algorithms but are an essential computational step in implementing rate-fair
and queue stabilizing scheduling policies in wireless networks. We consider a
belief propagation framework to solve such problems approximately. In
particular, we construct approximations to the belief propagation iterations to
obtain computationally simple and distributed algorithms with low communication
overhead. Notably, our methods are very general and apply to, for example, the
optimization of transmit powers, transmit beamforming vectors, and sub-band
allocation to maximize the above objective. Numerical results for femtocell
deployments demonstrate that such algorithms compute a very good operating
point in typically just a couple of iterations.
