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

• Published in: 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications pp. 1 - 5
• Main Authors: Yau Hee Kho, Taylor, D.P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2007
• Subjects: AWGN; Channel estimation; Frequency estimation; Land mobile radio; Least squares approximation; MIMO; Mobile communication; Polynomials; Receiving antennas; Rician channels
• ISBN: 9781424411436; 1424411432
• ISSN: 2166-9570
• DOI: 10.1109/PIMRC.2007.4394316

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.