OFDM channel estimation by singular value decomposition

Abstract

A new approach to low-complexity channel estimation in orthogonal-frequency division multiplexing (OFDM) systems is proposed. A low-rank approximation is applied to a linear minimum mean-squared error (LMMSE) estimator that uses the frequency correlation of the channel. By using the singular value decomposition (SVD) an optimal low-rank estimator is derived, where performance is essentially preserved-even for low computational complexities. A fixed estimator, with nominal values for channel correlation and signal-to-noise ratio (SNR), is analysed. Analytical mean-squared error (MSE) and symbol-error rates (SER) are presented for a 16-QAM OFDM system.