On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels

Lars P.B. Christensen; Jan Larsen

doi:10.1109/ICASSP.2006.1661006

On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels

Lars P.B. Christensen, Jan Larsen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

A general Variational Bayesian framework for iterative data and parameter estimation for coherent detection is introduced as a generalization of the EM-algorithm. Explicit solutions are given for MIMO channel estimation with Gaussian prior and noise covariance estimation with inverse-Wishart prior. Simulation of a GSM-like system provides empirical proof that the VBEM-algorithm is able to provide better performance than the EM-algorithm. However, if the posterior distribution is highly peaked, the VBEM-algorithm approaches the EM-algorithm and the gain disappears. The potential gain is therefore greatest in systems with a small amount of observations compared to the number of parameters to be estimated.

Original language	English
Title of host publication	IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Volume	4
Publisher	IEEE
Publication date	2006
ISBN (Print)	1-4244-0469-X
DOIs	https://doi.org/10.1109/ICASSP.2006.1661006
Publication status	Published - 2006
Event	2006 IEEE International Conference on Acoustics, Speech and Signal Processing - Toulouse, France Duration: 14 May 2006 → 19 May 2006 Conference number: 31

Conference

Conference	2006 IEEE International Conference on Acoustics, Speech and Signal Processing
Number	31
Country/Territory	France
City	Toulouse
Period	14/05/2006 → 19/05/2006

Bibliographical note

Copyright: 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

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title = "On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels",

abstract = "A general Variational Bayesian framework for iterative data and parameter estimation for coherent detection is introduced as a generalization of the EM-algorithm. Explicit solutions are given for MIMO channel estimation with Gaussian prior and noise covariance estimation with inverse-Wishart prior. Simulation of a GSM-like system provides empirical proof that the VBEM-algorithm is able to provide better performance than the EM-algorithm. However, if the posterior distribution is highly peaked, the VBEM-algorithm approaches the EM-algorithm and the gain disappears. The potential gain is therefore greatest in systems with a small amount of observations compared to the number of parameters to be estimated.",

author = "Christensen, {Lars P.B.} and Jan Larsen",

note = "Copyright: 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE; 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 ; Conference date: 14-05-2006 Through 19-05-2006",

year = "2006",

doi = "10.1109/ICASSP.2006.1661006",

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booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",

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Christensen, LPB & Larsen, J 2006, On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels. in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). vol. 4, IEEE, 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse, France, 14/05/2006. https://doi.org/10.1109/ICASSP.2006.1661006

On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels. / Christensen, Lars P.B.; Larsen, Jan.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Vol. 4 IEEE, 2006.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AB - A general Variational Bayesian framework for iterative data and parameter estimation for coherent detection is introduced as a generalization of the EM-algorithm. Explicit solutions are given for MIMO channel estimation with Gaussian prior and noise covariance estimation with inverse-Wishart prior. Simulation of a GSM-like system provides empirical proof that the VBEM-algorithm is able to provide better performance than the EM-algorithm. However, if the posterior distribution is highly peaked, the VBEM-algorithm approaches the EM-algorithm and the gain disappears. The potential gain is therefore greatest in systems with a small amount of observations compared to the number of parameters to be estimated.

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M3 - Article in proceedings

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BT - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Y2 - 14 May 2006 through 19 May 2006

ER -

On Data and Parameter Estimation Using the Variational Bayesian EM-algorithm for Block-fading Frequency-selective MIMO Channels

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