Reduced Complexity MIMO Channel Estimation and Equalization using a Polynomial-Predictor-based Vector GLMS Algorithm

Abstract

A reduced complexity multiple-input multiple-output (MIMO) channel estimator known as the polynomial-predictor-based vector generalized least mean squares (VGLMS) estimator is developed. It is a simplification of a previously developed polynomial-predictor-based vector generalized recursive least squares (VGRLS) estimator, achieved by replacing the online recursive computation of the 'intermediate' matrix by an offline pre-computed matrix. Similar to the VGRLS estimator, it is able to operate in Rayleigh or Rician fading environments without reconfiguration of the state transition matrix to accommodate the non-random mean components. It is seen to offer a trade-off between reduced complexity channel estimation and good system performance.

MIMO Receiver Using Reduced Complexity Sequence Estimation With Channel Estimation and Tracking

“…2 ) and results in a reduced complexity algorithm known as the vectorgeneralized least mean squares (VGLMS) estimator [18]. Thus, we have also simulated an integrated receiver that employs the VGLMS estimator and PVA algorithm.…”

“…We process a block of L f received signal vectors to obtain (18) and use the channel estimates to obtain the prefiltered channel tapsH k,n for n = 0, 1, . .…”