Location aided semi-blind interference alignment for clustered small cell networks

Abstract

We consider the applications of blind and semi-blind interference alignment in multicell scenarios, specifically in clustered small cells. As a first step, two simple straight forward extensions of blind interference alignment are examined and it is observed that neither of them is uniformly superior. Then, we propose exploiting the location information of the users and base stations in the cluster to enhance the performance of fully blind schemes for any given user distribution scenario. Our aim is to group suitable users that can be served at the same time to minimize the supersymbol length for each cluster. Since the defined problem is NP-hard, we propose a heuristic algorithm that can provide an effective solution without too much complexity. By numerical simulations, we show that the proposed semi blind algorithm, Top.BIA, uniformly performs better than pure blind interference alignment schemes for any possible user distribution scenario.