Two-Dimensional Pilot-Symbol-Aided Channel Estimation by Wiener Filtering
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
Mobile Fading Channels
EURASIP Journal on Applied Signal Processing
A fast LMMSE channel estimation method for OFDM systems
EURASIP Journal on Wireless Communications and Networking - Special issue on OFDMA architectures, protocols, and applications
SNR estimation algorithm based on the preamble for OFDM systems in frequency selective channels
IEEE Transactions on Communications
Channel estimation in OFDM systems with unknown interference
IEEE Transactions on Wireless Communications
A comparison of pilot-aided channel estimation methods for OFDMsystems
IEEE Transactions on Signal Processing
Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals
IEEE Transactions on Signal Processing
Linear Interpolation in Pilot Symbol Assisted Channel Estimation for OFDM
IEEE Transactions on Wireless Communications
On the asymptotic eigenvalue distribution of Toeplitz matrices
IEEE Transactions on Information Theory
| Hi-index | 0.08 |
This paper proposes a linear minimum mean square error-based (LMMSE) channel estimation method, which allows avoiding the necessary knowledge of the channel covariance matrix or its estimation. To do so, a perfectly tunable filter acting like an artificial channel is added at the receiver side. We show that an LMMSE estimation of the sum of this artificial channel and the physical channel only needs the covariance matrix of the artificial channel, and the channel estimation is finally obtained by subtracting the frequency coefficients of the added filter. We call this method artificial channel aided-LMMSE (ACA-LMMSE). Theoretical developments and simulations prove that its performance is close to theoretical LMMSE, and we show that this method reduces the computational complexity, compared to usual LMMSE, due to the covariance matrix used for ACA-LMMSE is computed only once throughout the transmission duration. We put the conditions on the artificial channel parameters to get the expected mask effect. Simulations display the performance of the proposed method, in terms of MMSE and bit error rate (BER). Indeed, the difference of BER between our method and the theoretical LMMSE is less than 2dB.