Iterative interference alignment in macrocell-femtocell networks: A cognitive radio approach

Abstract

The deployment of femtocells in current and future communication systems promises an effective solution for limited indoor coverage problem and a possible gateway for mobile data offloading. In this paper, we cast a cognitive interference alignment approach (IA) suitable for heterogeneous cellular networks with a mixed macrocell and femtocell deployment Specifically, in our approach a restricted waterfilling (RWF) algorithm is used to maximize the downlink data rate, while reserving some eigenmodes for giving the femtocell basestations the opportunity to do their transmissions even at high signal-to-noise power ratio (SNR) for the macrocell basestation. Additionally, both the cross-tier and co-tier interference is to be aligned at each femtocell user's receiver using an Iterative Reweighted Least Squares(IRLS) algorithm. The simulation results show that the proposed IA approach provides an improved sum rate for the femtocell users, compared to the conventional IA techniques, like, the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach.