Partially Connected Multi-cell Interference Broadcast Channels Based Iterative Interference Alignment with Imperfect Channel Knowledge

Abstract

Interference alignment (IA) has been proved in theory that it can be achievable in a partially connected multi-cell MIMO interfering broadcast channels (IBC) network of arbitrary size, while the signaling dimension of each transmit and receive antennas pair between base station (BS) and user remains bound. For this applicable significance, based on the L-interfering MIMO IBC model, two iterative IA algorithms are presented to solve the alignment problem for this type of network in this paper. Then the feasibility conditions and the impact of channel knowledge imperfection for the proposed algorithms are analyzed. Simulations show that, with a finite antenna number per transmitter and receiver pair, the proposed algorithms can achieve the optimal degrees of freedom (DoF) and can be applied to a partially connected multi-cell MIMO IBC network with arbitrary number of cells and users per cell. Meanwhile, the proposed algorithms are sensitive to imperfect channel knowledge, especially in high SNR region.