  We propose a simple and fast method for providing a high quality solution for
the sum-interference minimization problem. As future networks are deployed in
high density urban areas, improved clustering methods are needed to provide low
interference network connectivity. The proposed algorithm applies
straightforward similarity based clustering and optionally stable matchings to
outperform state of the art algorithms. The running times of our algorithms are
dominated by one matrix multiplication.
