Eigenvector decomposition (EVD) is an inevitable operation to obtain the
precoders in practical massive multiple-input multiple-output (MIMO) systems.
Due to the large antenna size and at finite computation resources at the base
station (BS), the overwhelming computation complexity of EVD is one of the key
limiting factors of the system performance. To address this problem, we propose
an eigenvector prediction (EGVP) method by interpolating the precoding matrix
with predicted eigenvectors. The basic idea is to exploit a few historical
precoders to interpolate the rest of them without EVD of the channel state
information (CSI). We transform the nonlinear EVD into a linear prediction
problem and prove that the prediction of the eigenvectors can be achieved with
a complex exponential model. Furthermore, a channel prediction method called
fast matrix pencil prediction (FMPP) is proposed to cope with the CSI delay
when applying the EGVP method in mobility environments. The asymptotic analysis
demonstrates how many samples are needed to achieve asymptotically error-free
eigenvector predictions and channel predictions. Finally, the simulation
results demonstrate the spectral efficiency improvement of our scheme over the
benchmarks and the robustness to different mobility scenarios.Comment: 13pages, 7 figures, 1 table, journa