Low-complexity eigenvector prediction-based precoding matrix prediction in massive MIMO with mobility

TL;DR

This paper introduces a low-complexity eigenvector prediction method for precoding in massive MIMO systems with mobility, significantly reducing computational load while maintaining or improving spectral efficiency.

Contribution

It proposes a novel eigenvector prediction approach based on channel eigenvector decomposition and exponential interpolation, with a fast matrix pencil prediction for CSI, achieving asymptotically error-free precoding.

Findings

Reduces floating point operations by 80% under perfect CSI.

Achieves spectral efficiency gains with CSI delays.

Provides asymptotically error-free precoder prediction.

Abstract

In practical massive multiple-input multiple-output (MIMO) systems, the precoding matrix is often obtained from the eigenvectors of channel matrices and is challenging to update in time due to finite computation resources at the base station, especially in mobile scenarios. In order to reduce the precoding complexity while enhancing the spectral efficiency (SE), a novel precoding matrix prediction method based on the eigenvector prediction (EGVP) is proposed. The basic idea is to decompose the periodic uplink channel eigenvector samples into a linear combination of the channel state information (CSI) and channel weights. We further prove that the channel weights can be interpolated by an exponential model corresponding to the Doppler characteristics of the CSI. A fast matrix pencil prediction (FMPP) method is also devised to predict the CSI. We also prove that our scheme achieves asymptotically error-free precoder prediction with a distinct complexity advantage. Simulation results show that under the perfect non-delayed CSI, the proposed EGVP method reduces floating point operations by 80\% without losing SE performance compared to the traditional full-time precoding scheme. In more realistic cases with CSI delays, the proposed EGVP-FMPP scheme has clear SE performance gains compared to the precoding scheme widely used in current communication systems.