Belief propagation methods for intercell interference coordination in femtocell networks

Interference coordination is a fundamental challenge in emerging femtocellular deployments. This paper considers a broad class of interference coordination and resource allocation problems for wireless links based on utility maximization with a general linear mixing interference model suitable for complex femtocellular systems. 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, semi-static and dynamic interference coordination problems including the optimization of transmit powers, transmit beamforming vectors, fractional frequency reuse (FFR) and sub-band allocations 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.