The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kajian ini bertujuan untuk meneroka kaedah penumpuan cepat penyamaan buta menggunakan statistik tertib tinggi (kumulan). Usaha ini tertumpu pada mendapatkan penyelesaian teori baharu untuk penyamaan buta daripada menyiasat algoritma praktikal. Di bawah andaian biasa untuk rangka kerja ini, didapati bahawa syarat untuk penyamaan buta dikaitkan secara langsung dengan masalah eigen, iaitu pekali ketinggalan penyamaan boleh diperolehi daripada vektor eigen bagi matriks statistik tertib lebih tinggi. Kaedah pemulihan fasa buta juga dicadangkan untuk sistem QAM. Simulasi komputer menunjukkan bahawa penumpuan yang sangat cepat boleh dicapai berdasarkan pendekatan.
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Salinan
Ling CHEN, Hiroji KUSAKA, Masanobu KOMINAMI, "Blind Channel Equalization and Phase Recovery Using Higher Order Statistics and Eigendecomposition" in IEICE TRANSACTIONS on Communications,
vol. E82-B, no. 7, pp. 1048-1054, July 1999, doi: .
Abstract: This study is aimed to explore a fast convergence method of blind equalization using higher order statistics (cumulants). The efforts are focused on deriving new theoretical solutions for blind equalizers rather than investigating practical algorithms. Under the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i. e. the lag coefficients of the equalizer can be obtained from the eigenvectors of a higher order statistics matrix. A method of blind phase recovery is also proposed for QAM systems. Computer simulations show that very fast convergence can be achieved based on the approach.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e82-b_7_1048/_p
Salinan
@ARTICLE{e82-b_7_1048,
author={Ling CHEN, Hiroji KUSAKA, Masanobu KOMINAMI, },
journal={IEICE TRANSACTIONS on Communications},
title={Blind Channel Equalization and Phase Recovery Using Higher Order Statistics and Eigendecomposition},
year={1999},
volume={E82-B},
number={7},
pages={1048-1054},
abstract={This study is aimed to explore a fast convergence method of blind equalization using higher order statistics (cumulants). The efforts are focused on deriving new theoretical solutions for blind equalizers rather than investigating practical algorithms. Under the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i. e. the lag coefficients of the equalizer can be obtained from the eigenvectors of a higher order statistics matrix. A method of blind phase recovery is also proposed for QAM systems. Computer simulations show that very fast convergence can be achieved based on the approach.},
keywords={},
doi={},
ISSN={},
month={July},}
Salinan
TY - JOUR
TI - Blind Channel Equalization and Phase Recovery Using Higher Order Statistics and Eigendecomposition
T2 - IEICE TRANSACTIONS on Communications
SP - 1048
EP - 1054
AU - Ling CHEN
AU - Hiroji KUSAKA
AU - Masanobu KOMINAMI
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E82-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 1999
AB - This study is aimed to explore a fast convergence method of blind equalization using higher order statistics (cumulants). The efforts are focused on deriving new theoretical solutions for blind equalizers rather than investigating practical algorithms. Under the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i. e. the lag coefficients of the equalizer can be obtained from the eigenvectors of a higher order statistics matrix. A method of blind phase recovery is also proposed for QAM systems. Computer simulations show that very fast convergence can be achieved based on the approach.
ER -