  For networks of systems, with possibly improper transfer function matrices,
we present a design framework which enables $\mathcal{H}_\infty$ control, while
imposing sparsity constraints on the controller's coprime factors. We propose a
convex and iterative optimization procedure with guaranteed convergence to
obtain distributed controllers. By exploiting the robustness-oriented nature of
our proposed approach, we provide the means to obtain sparse representations of
our control laws that may not be directly supported by the network's nominal
model.
