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Eigenvector decomposition (EVD) is an inevitable operation to obtain theprecoders in practical massive multiple-input multiple-output (MIMO) systems.Due to the large antenna size and at finite computation resources at the basestation (BS), the overwhelming computation complexity of EVD is one of the keylimiting factors of the system performance. To address this problem, we proposean eigenvector prediction (EGVP) method by interpolating the precoding matrixwith predicted eigenvectors. The basic idea is to exploit a few historicalprecoders to interpolate the rest of them without EVD of the channel stateinformation (CSI). We transform the nonlinear EVD into a linear predictionproblem and prove that the prediction of the eigenvectors can be achieved witha complex exponential model. Furthermore, a channel prediction method calledfast matrix pencil prediction (FMPP) is proposed to cope with the CSI delaywhen applying the EGVP method in mobility environments. The asymptotic analysisdemonstrates how many samples are needed to achieve asymptotically error-freeeigenvector predictions and channel predictions. Finally, the simulationresults demonstrate the spectral efficiency improvement of our scheme over thebenchmarks and the robustness to different mobility scenarios.

Eigenvector prediction-based precoding for massive MIMO with mobility