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

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 sq...

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Bibliographic Details
Published in2007 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
LanguageEnglish
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
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ISBN9781424411436
1424411432
ISSN2166-9570
DOI10.1109/PIMRC.2007.4394316

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Summary: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.
ISBN:9781424411436
1424411432
ISSN:2166-9570
DOI:10.1109/PIMRC.2007.4394316