  Small cell enchantment is emerging as the key technique for wireless network
evolution. One challenging problem for small cell enhancement is how to achieve
high data rate with as-low-as-possible control and computation overheads. As a
solution, we propose a low-complexity distributed optimization framework in
this paper. Our solution includes two parts. One is a novel implicit
information exchange mechanism that enables channel-aware opportunistic
scheduling and resource allocation among links. The other is the sub-gradient
based algorithm with a polynomial-time complexity. What is more, for large
scale systems, we design an improved distributed algorithm based on insights
obtained from the problem structure. This algorithm achieves a close-to-optimal
performance with a much lower complexity. Our numerical evaluations validate
the analytical results and show the advantage of our algorithms.
