Resource management for two-tier femtocell networks using interference alignment

In this paper, we propose a novel interference management solution for a two-tier femtocell network by using the interference alignment (IA) technique. The developed solution aims to maximize the total throughput for femtocells and support required minimum signal to interference plus noise ratios (SINRs) for macro user equipments (MUEs). The framework requires only limited cooperation between MUEs and femto BSs (FBSs) where we manage to formulate and transform the IA-based cross-tier interference control problem into a nice convex form. This problem can determine the precoding and decoding vectors for MUEs and the macro BS (MBS) so that the cross-tier interference that MUEs create for the femto tier is confined in the minimum number of subspaces. Then, we devise two noniterative algorithms to determine the precoding and decoding vectors for femto user equipments (FUEs) and FBSs. Since these two algorithms only work efficiently in different regimes where the cross-tier interference from MUEs to the femto tier is large or small, respectively, we develop an adaptive algorithm performing well in both regimes. Finally, we present numerical results to demonstrate the efficacy of our proposed algorithms in comparison with existing IA solutions in the literature.