OFDM channel estimation by singular value decomposition

Ove Edfors; Magnus Sandell; Jan-Jaap van de Beek; Sarah Kate Wilson; Per Ola Börjesson

doi:10.1109/26.701321

OFDM channel estimation by singular value decomposition

Ove Edfors, Magnus Sandell, Jan-Jaap van de Beek, Sarah Kate Wilson, Per Ola Börjesson

Department of Electrical and Information Technology

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

Abstract

We present and analyze low-rank channel estimators for orthogonal frequency-division multiplexing (OFDM) systems using the frequency correlation of the channel. Low-rank approximations based on the discrete Fourier transform (DFT) have been proposed, but these suffer from poor performance when the channel is not sample spaced. We apply the theory of optimal rank-reduction to linear minimum mean-squared error (LMMSE) estimators and show that these estimators, when using a fixed design, are robust to changes in channel correlation and signal-to-noise ratio (SNR). The performance is presented in terms of uncoded symbol-error rate (SER) for a system using 16-quadrature amplitude modulation (QAM)

Original language	English
Pages (from-to)	931-939
Journal	IEEE Transactions on Communications
Volume	47
Issue number	7
DOIs	https://doi.org/10.1109/26.701321
Publication status	Published - 1998

Subject classification (UKÄ)

Electrical Engineering, Electronic Engineering, Information Engineering

Access to Document

10.1109/26.701321

Cite this

@article{18fe6565a7114ac28a6429a23a91a4d3,

title = "OFDM channel estimation by singular value decomposition",

abstract = "We present and analyze low-rank channel estimators for orthogonal frequency-division multiplexing (OFDM) systems using the frequency correlation of the channel. Low-rank approximations based on the discrete Fourier transform (DFT) have been proposed, but these suffer from poor performance when the channel is not sample spaced. We apply the theory of optimal rank-reduction to linear minimum mean-squared error (LMMSE) estimators and show that these estimators, when using a fixed design, are robust to changes in channel correlation and signal-to-noise ratio (SNR). The performance is presented in terms of uncoded symbol-error rate (SER) for a system using 16-quadrature amplitude modulation (QAM)",

author = "Ove Edfors and Magnus Sandell and {van de Beek}, Jan-Jaap and Wilson, {Sarah Kate} and B{\"o}rjesson, {Per Ola}",

year = "1998",

doi = "10.1109/26.701321",

language = "English",

volume = "47",

pages = "931--939",

journal = "IEEE Transactions on Communications",

issn = "0090-6778",

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

number = "7",

}

TY - JOUR

T1 - OFDM channel estimation by singular value decomposition

AU - Edfors, Ove

AU - Sandell, Magnus

AU - van de Beek, Jan-Jaap

AU - Wilson, Sarah Kate

AU - Börjesson, Per Ola

PY - 1998

Y1 - 1998

N2 - We present and analyze low-rank channel estimators for orthogonal frequency-division multiplexing (OFDM) systems using the frequency correlation of the channel. Low-rank approximations based on the discrete Fourier transform (DFT) have been proposed, but these suffer from poor performance when the channel is not sample spaced. We apply the theory of optimal rank-reduction to linear minimum mean-squared error (LMMSE) estimators and show that these estimators, when using a fixed design, are robust to changes in channel correlation and signal-to-noise ratio (SNR). The performance is presented in terms of uncoded symbol-error rate (SER) for a system using 16-quadrature amplitude modulation (QAM)

AB - We present and analyze low-rank channel estimators for orthogonal frequency-division multiplexing (OFDM) systems using the frequency correlation of the channel. Low-rank approximations based on the discrete Fourier transform (DFT) have been proposed, but these suffer from poor performance when the channel is not sample spaced. We apply the theory of optimal rank-reduction to linear minimum mean-squared error (LMMSE) estimators and show that these estimators, when using a fixed design, are robust to changes in channel correlation and signal-to-noise ratio (SNR). The performance is presented in terms of uncoded symbol-error rate (SER) for a system using 16-quadrature amplitude modulation (QAM)

U2 - 10.1109/26.701321

DO - 10.1109/26.701321

M3 - Article

SN - 0090-6778

VL - 47

SP - 931

EP - 939

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

IS - 7

ER -

OFDM channel estimation by singular value decomposition

Abstract

Subject classification (UKÄ)

Access to Document

Fingerprint

Cite this