EM-based channel estimation algorithms for OFDM
EURASIP Journal on Applied Signal Processing
An ML-based estimate and the Cramer-Rao bound for data-aided channel estimation in KSP-OFDM
EURASIP Journal on Wireless Communications and Networking - Multicarrier Systems
Estimation and equalization of doubly selective channels using known symbol padding
IEEE Transactions on Signal Processing
Gaussian maximum-likelihood channel estimation with short training sequences
IEEE Transactions on Wireless Communications
New high-rate wireless LAN standards
IEEE Communications Magazine
Transmission techniques for digital terrestrial TV broadcasting
IEEE Communications Magazine
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In this correspondence, we propose an iterative "turbo" channel estimation algorithm for known symbol padding (KSP) orthogonal frequency-division multiplexing (OFDM), where the guard interval is filled with pilot symbols. Additional pilot symbols are transmitted on some of the OFDM carriers. The channel estimation algorithm is based on the expectation-maximization (EM) algorithm. In the initialization phase of this iterative algorithm, the received time-domain samples are first converted to the frequency domain, and the initial channel estimate is based on the observation of the pilot carriers only. Then the EM-algorithm switches back to the time-domain and updates the channel estimates until convergence is reached. The proposed estimator performs very good: the mean square error (MSE) performance of the proposed estimator is close to the Cramér-Rao lower bound (CRB) corresponding to the all pilots case, for the SNR region of practical interest, and the resulting bit error rate essentially coincides with the case of the perfectly known channel.