IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
IEEE Transactions on Signal Processing
Recursive MMSE channel estimation for MIMO-OFDM systems
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Achievable throughput enhancement based on modified carrier interferometry for MIMO/OFDM
Digital Signal Processing
HTRCI and Channel Ranking Based Joint Symbols Detection for MQRD-PCM/MIMO-OFDM
Wireless Personal Communications: An International Journal
An Enhanced Embedded-Pilot Channel Estimation Architecture for MIMO MC-CDMA Systems
Wireless Personal Communications: An International Journal
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Multiple-input multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems employing coherent receivers crucially require channel state information (CSI). Since the multipath delay profile of channels is arbitrary in the MIMO-OFDM systems, an effective channel estimator is needed. In this paper, we first develop a pilot-embedded data-bearing (PEDB) approach for joint channel estimation and data detection, in which PEDB least-square (LS) channel estimator and maximum-likelihood (ML) data detection are employed. Then, we propose an LS fast Fourier transform (FFT)-based channel estimator by employing the concept of FFT-based channel estimation to improve the PEDB-LS one via choosing a certain number of significant taps for constructing a channel frequency response. The effects of model mismatch error inherent in the proposed LS FFT-based estimator when considering noninteger multipath delay profiles and its performance analysis are investigated. The relationship between the mean-squared error (MSE) and the number of chosen significant taps is revealed, and hence, the optimal criterion for obtaining the optimum number of significant taps is explored. Under the framework of pilot embedding, we further propose an adaptive LS FFT-based channel estimator employing the optimum number of significant taps to compensate the model mismatch error as well as minimize the corresponding noise effect. Simulation results reveal that the adaptive LS FFT-based estimator is superior to the LS FFT-based and PEDB-LS estimators under quasi-static channels or low Doppler's shift regimes