Weighted fast iterative shrinkage thresholding for 3D massive MIMO channel estimation

Abstract

Fitting the huge number of pilots needed for massive multiple inputs multiple outputs antennas (MIMO) channel estimation within the available time and frequency resources is a challenging problem. Generally, compressed sensing (CS) channel estimation algorithms face the dilemma of trading off the estimation accuracy and the computational complexity. In this paper, we propose a weighted fast iterative shrinkage thresholding algorithm (W-FISTA). The proposed algorithm provides higher estimation efficiency with the same complexity as the original FISTA. With low computational complexity, multiple measurement vectors (MMV) version of the W-FISTA is proposed to estimate the 3D massive MIMO channel. The proposed MMV-WFISTA estimate the channel coefficients by exploiting its joint sparsity structure in the angle-delay sparse domain. The complexity analysis and the simulation results indicate a clear improvement in the performance of the proposed MMV-WFISTA over joint estimation algorithms.