A Large-Scale MIMO Precoding Algorithm Based on Iterative Interference Alignment

The performance of Large-scale MIMO system is degraded by Pilot Contamination. In order to reduce Pilot Contamination, a downlink precoding algorithm is put forward, based on Interference Alignment (IA). The main idea of this algorithm is aligning the pilot contamination and inter-cell interference to the same null space in order to acquire the maximal degrees of freedom. Then the downlink receiving precoding matrix is solved with respect to a maximal SINR (Signal Interference Noise Ratio) criterion. Exploiting the channel reciprocity and an iterative process, Base station and User Equipment switch transmitting and receiving roles in the uplink and downlink, the precoding matrices of the Base station and User Equipment is gradually updated until convergence. Finally, the simulation results have shown that the algorithm proposed can efficiently mitigate the impact of pilot contamination and outperform some popular precoding algorithms, e.g., MF precoding algorithm and MMSE precoding algorithm. When the number of antennas increases, the performance of the proposed algorithm will be greatly improved.