Dominant Path Zero-Forcing Based on Low-Rank Matrix Approximation for Full-Dimensional Massive MIMO Systems

The conventional zero-forcing (ZF) precoding and the two dimensional (2D) ZF precoding are two popular schemes to cancel the interference in the downlink of the full-dimensional (FD) massive MIMO systems. However, the conventional ZF is of high complexity as a result of ignoring the structure of the FD massive MIMO channels while the 2D ZF has poor performance due to neglecting the elevation angular spread. In this correspondence, by exploiting the spatial correlation of the FD massive MIMO channels, we propose a dominant path zero-forcing precoding (DPZF) scheme based on the low-rank matrix approximation. The proposed DPZF scheme includes two stages. In the first stage, we obtain the elevation and the azimuth components of r dominant paths for each user's channel by solving the rank-r channel matrix approximation. In the subsequent stage, we reformulate the Gram matrix with the obtained components so as to zero force the most dominant path of each user's channel with low complexity. For the proposed DPZF, the upper bound of the performance gap to the conventional ZF is derived and the complexity is analyzed. The analysis and simulation results indicate that the proposed DPZF can yield a more elegant performance-complexity tradeoff than the existing precoding schemes.