Blind spatial signature estimation using time-varying user power loading and parallel factor analysis

Yue Rong; Sergiy A. Vorobyov; Alex B. Gershman; Nicholas D. Sidiropoulos

Blind spatial signature estimation using time-varying user power loading and parallel factor analysis

Yue Rong, Sergiy A. Vorobyov, Alex B. Gershman, Nicholas D. Sidiropoulos

Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

The problem of blind user spatial signature estimation using the parallel factor (PARAFAC) analysis model is addressed in the context of applications to wireless communications. A time-varying user power loading hi the uplink mode is proposed to enable identifiability and application of PARAFAC analysis. Identifiability issues are carefully studied and two blind spatial signature estimation algorithms are developed. The first technique is based on the PARAFAC fitting trilinear alternating least squares (TALS) regression procedure, while the second one makes use of the joint approximate diagonalization algorithm. These techniques do not require any knowledge of the propagation channel and/or sensor array manifold and are applicable to a more general class of scenarios than earlier blind approaches to spatial signature estimation.

Original language	English (US)
Pages (from-to)	79-83
Number of pages	5
Journal	IEEE Vehicular Technology Conference
Volume	58
Issue number	1
State	Published - Dec 1 2003
Event	2003 IEEE 58th Vehicular Technology Conference, VTC2003-Fall - Orlando, FL, United States Duration: Oct 6 2003 → Oct 9 2003

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title = "Blind spatial signature estimation using time-varying user power loading and parallel factor analysis",

abstract = "The problem of blind user spatial signature estimation using the parallel factor (PARAFAC) analysis model is addressed in the context of applications to wireless communications. A time-varying user power loading hi the uplink mode is proposed to enable identifiability and application of PARAFAC analysis. Identifiability issues are carefully studied and two blind spatial signature estimation algorithms are developed. The first technique is based on the PARAFAC fitting trilinear alternating least squares (TALS) regression procedure, while the second one makes use of the joint approximate diagonalization algorithm. These techniques do not require any knowledge of the propagation channel and/or sensor array manifold and are applicable to a more general class of scenarios than earlier blind approaches to spatial signature estimation.",

author = "Yue Rong and Vorobyov, {Sergiy A.} and Gershman, {Alex B.} and Sidiropoulos, {Nicholas D.}",

year = "2003",

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language = "English (US)",

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journal = "IEEE Vehicular Technology Conference",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "2003 IEEE 58th Vehicular Technology Conference, VTC2003-Fall ; Conference date: 06-10-2003 Through 09-10-2003",

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T1 - Blind spatial signature estimation using time-varying user power loading and parallel factor analysis

AU - Rong, Yue

AU - Vorobyov, Sergiy A.

AU - Gershman, Alex B.

AU - Sidiropoulos, Nicholas D.

PY - 2003/12/1

Y1 - 2003/12/1

N2 - The problem of blind user spatial signature estimation using the parallel factor (PARAFAC) analysis model is addressed in the context of applications to wireless communications. A time-varying user power loading hi the uplink mode is proposed to enable identifiability and application of PARAFAC analysis. Identifiability issues are carefully studied and two blind spatial signature estimation algorithms are developed. The first technique is based on the PARAFAC fitting trilinear alternating least squares (TALS) regression procedure, while the second one makes use of the joint approximate diagonalization algorithm. These techniques do not require any knowledge of the propagation channel and/or sensor array manifold and are applicable to a more general class of scenarios than earlier blind approaches to spatial signature estimation.

AB - The problem of blind user spatial signature estimation using the parallel factor (PARAFAC) analysis model is addressed in the context of applications to wireless communications. A time-varying user power loading hi the uplink mode is proposed to enable identifiability and application of PARAFAC analysis. Identifiability issues are carefully studied and two blind spatial signature estimation algorithms are developed. The first technique is based on the PARAFAC fitting trilinear alternating least squares (TALS) regression procedure, while the second one makes use of the joint approximate diagonalization algorithm. These techniques do not require any knowledge of the propagation channel and/or sensor array manifold and are applicable to a more general class of scenarios than earlier blind approaches to spatial signature estimation.

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T2 - 2003 IEEE 58th Vehicular Technology Conference, VTC2003-Fall

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