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In this paper, partial data-dependent superimposed training based channel estimation for OFDM systems over doubly selective channels (DSCs) is addressed. Due to the presence of unknown data as interference, we first derive a minimum mean square error (MMSE) channel estimator by treating the effect of unknown data as noise. To further improve the performance, a novel iterative algorithm which jointly...
In this paper the effect of CFO (carrier frequency offset) on channel estimation in OFDM systems is investigated. The LMMSE channel estimation is considered and it is shown that CFO degrades the performance of this algorithm. In addition a novel method called ICA-LMMSE is proposed. It uses ICA (independent component analysis) to find an estimate of CFO, in order to cancel out the inefficiency caused...
Existing DD estimators in OFDM systems do not appropriately reduce the influence brought by incorrect decision, and hence suffer from error propagation. In order to mitigate the error propagation in DD channel estimation, a novel DD channel estimator based on recursive linear minimum mean-square error (LMMSE) is proposed. The algorithm takes the error vector of previous channel state information (CSI)...
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