Linear Space-Time Interference Alignment for $K$ -User MIMO Interference Channels

Abstract

Interference is believed to be the most significant bottleneck for the next-generation wireless networks to achieve high throughout. Interference alignment (IA), as a novel interference management scheme to break through the traditional interference cancelation, not only makes the complete mitigation of interference possible but also achieves a theoretical breakthrough in promoting the wireless network capacity region. In this paper, by combining the space and time, we proposed a linear space-time (LST) IA algorithm based on the extension of the channel in time dimension for $K$ -user multi-input multi-output interference channel. The proposed LST-IA scheme effectively reduces the number of antennas required for eliminating interference completely in systems, and the closed-form solution of precoding matrices and detector matrices is obtained as well. Compared with the classical IA algorithms, the simulation results demonstrate that the proposed scheme shows distinguished advantages in terms of sum-rate and bit error rate in the strong interference communication scenarios.