Finite-length MIMO equalization using canonical correlation analysis

Aleksandar Dogandžić; Arye Nehorai

doi:10.1109/78.992151

Finite-length MIMO equalization using canonical correlation analysis

Aleksandar Dogandžić
, Arye Nehorai

Research output: Contribution to journal › Article › peer-review

26 Scopus citations

Abstract

Finite-length multi-input multi-output (MIMO) equalization methods for smart antennas were proposed using the statistical theory of canonical correlations. A relationship between the proposed methods and the maximum likelihood (ML) reduced-rank channel and noise estimation for the unknown spatially correlated noise was shown. The joint equalization and symbol detection was applied to the received data by maximizing the concentrated likelihood, when the training data was unavailable.

Original language	English
Pages (from-to)	984-989
Number of pages	6
Journal	IEEE Transactions on Signal Processing
Volume	50
Issue number	4
DOIs	https://doi.org/10.1109/78.992151
State	Published - Apr 2002

Keywords

MIMO equalization
Space-time processing

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10.1109/78.992151

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title = "Finite-length MIMO equalization using canonical correlation analysis",

abstract = "Finite-length multi-input multi-output (MIMO) equalization methods for smart antennas were proposed using the statistical theory of canonical correlations. A relationship between the proposed methods and the maximum likelihood (ML) reduced-rank channel and noise estimation for the unknown spatially correlated noise was shown. The joint equalization and symbol detection was applied to the received data by maximizing the concentrated likelihood, when the training data was unavailable.",

keywords = "MIMO equalization, Space-time processing",

author = "Aleksandar Dogand{\v z}i{\'c} and Arye Nehorai",

year = "2002",

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AU - Dogandžić, Aleksandar

AU - Nehorai, Arye

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N2 - Finite-length multi-input multi-output (MIMO) equalization methods for smart antennas were proposed using the statistical theory of canonical correlations. A relationship between the proposed methods and the maximum likelihood (ML) reduced-rank channel and noise estimation for the unknown spatially correlated noise was shown. The joint equalization and symbol detection was applied to the received data by maximizing the concentrated likelihood, when the training data was unavailable.

AB - Finite-length multi-input multi-output (MIMO) equalization methods for smart antennas were proposed using the statistical theory of canonical correlations. A relationship between the proposed methods and the maximum likelihood (ML) reduced-rank channel and noise estimation for the unknown spatially correlated noise was shown. The joint equalization and symbol detection was applied to the received data by maximizing the concentrated likelihood, when the training data was unavailable.

KW - MIMO equalization

KW - Space-time processing

UR - https://www.scopus.com/pages/publications/0036538535

U2 - 10.1109/78.992151

DO - 10.1109/78.992151

M3 - Article

AN - SCOPUS:0036538535

SN - 1053-587X

VL - 50

SP - 984

EP - 989

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

IS - 4

ER -

Finite-length MIMO equalization using canonical correlation analysis

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Keywords

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