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Channel estimation techniques for OFDM systems in dispersive time-varying channels Song, Xuegui
Abstract
Coherent modulation is more effective than differential modulation for orthogonal frequency division multiplexing (OFDM) systems requiring high data rate and spectral efficiency. Channel estimation is therefore an integral part of the receiver design. In this thesis, two iterative maximum likelihood based channel estimation algorithms are proposed for an OFDM system in dispersive time-varying channels. A multipath channel model is proposed for OFDM uplink transmission in macrocellular systems. The multipath fading channel is modeled such that the channel state can be determined by estimating the unknown channel parameters. A second-order Taylor series expansion is adopted to simplify the channel estimation problem. Based on the system model, an iterative maximum likelihood based algorithm is first proposed to estimate the discrete-time channel parameters. The mean square error performance of the proposed algorithm is analyzed using a small perturbation technique. Based on a convergence rate analysis, an improved iterative maximum likelihood based channel estimation algorithm is presented using a successive overrelaxation method. Numerical experiments are performed to confirm the theoretical analyses and show the improvement in convergence rate of the improved algorithm.
Item Metadata
Title |
Channel estimation techniques for OFDM systems in dispersive time-varying channels
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2009
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Description |
Coherent modulation is more effective than differential modulation for orthogonal frequency division multiplexing (OFDM) systems requiring high data rate and spectral efficiency. Channel estimation is therefore an integral part of the receiver design. In this thesis, two iterative maximum likelihood based channel estimation algorithms are proposed for an OFDM system in dispersive time-varying channels. A multipath channel model is proposed for OFDM uplink transmission in macrocellular systems. The multipath fading channel is modeled such that the channel state can be determined by estimating the unknown channel parameters. A second-order Taylor series expansion is adopted to simplify the channel estimation problem. Based on the system model, an iterative maximum likelihood based algorithm is first proposed to estimate the discrete-time channel parameters. The mean square error performance of the proposed algorithm is analyzed using a small perturbation technique. Based on a convergence rate analysis, an improved iterative maximum likelihood based channel estimation algorithm is presented using a successive overrelaxation method. Numerical experiments are performed to confirm the theoretical analyses and show the improvement in convergence rate of the improved algorithm.
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Extent |
629817 bytes
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Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2009-06-09
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0067250
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2009-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International