Title :
OFDM channel estimation by singular value decomposition
Author :
Edfors, Ove ; Sandell, Magnus ; Van de Beek, Jan-Jaap ; Wilson, Sarah Kate ; Börjesson, Per Ola
Author_Institution :
Dept. of Appl. Electron., Lund Univ., Sweden
fDate :
7/1/1998 12:00:00 AM
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)
Keywords :
Gaussian channels; amplitude modulation; approximation theory; correlation methods; digital radio; discrete Fourier transforms; error statistics; fading; frequency division multiplexing; noise; parameter estimation; singular value decomposition; 16-QAM; 16-quadrature amplitude modulation; DFT; LMMSE; OFDM channel estimation; OFDM systems; SNR; channel correlation; discrete Fourier transform; fixed design; linear minimum mean-squared error; low-rank approximations; low-rank channel estimators; optimal rank-reduction; orthogonal frequency-division multiplexing; parallel Gaussian channels; performance; signal-to-noise ratio; singular value decomposition; uncoded symbol-error rate; wireless digital communications; Amplitude modulation; Channel estimation; Discrete Fourier transforms; Frequency division multiplexing; Frequency estimation; OFDM; Robustness; Signal design; Signal to noise ratio; Singular value decomposition;
Journal_Title :
Communications, IEEE Transactions on
