In this paper, we design a practical time-reversal quasi-orthogonal space-time block code (TR-QO-STBC) system for broadband multi-input multi-output (MIMO) communications. We first modify the TR-QO-STBC encoding structure so that the interference between the transmitted blocks can be completely removed by linear processing. Two low complex decision-feedback equalization (DFE) schemes are then proposed. One is built from the frequency-domain decision-feedback equalization (FD-DFE). The derived bi-directive FD-DFE (BiD-FD-DFE) cancels the interference among the successive symbols along the time axis. The other one is the enhanced V-BLAST, which cancels the interference between the real and imaginary parts of the spectral components. They have distinct performance characteristics due to the different interference-cancellation strategies. The underlying orthogonal and symmetric characters of TR-QO-STBC are exploited to reduce the computational complexity. Computer simulations confirm that the proposed equalizers can achieve better performance than the existing schemes.

In this letter, we propose a novel frequency-domain equalization (FDE) scheme for single-carrier multiple-input multiple-output (MIMO) systems over time-varying channels. Based on frequency-domain decision-feedback equalization (FD-DFE), we design a feedforward filter with constraint such that the equalization can be easily realized segment-by-segment with the help of the overlap-save (OLS) method. Since the segment length and block length can be designed independently, our proposal sets relatively short segment length to obtain good performance in time-varying environments, and very long block length to achieve high spectral efficiency. Furthermore, we present two scenarios in the design of filters for MIMO systems.

In this letter, we propose a novel frequency-domain equalizer (FDE) for single-carrier systems characterized by severe inter-symbol interference (ISI) channels; it consists of a linear FDE and an iterative block noise-predictor (IBNP). Unlike the FDE with time-domain noise predictor (FDE-NP), the proposed scheme allows the feedback equalizer being an uncausal filter, and performs the noise prediction in an iterative manner. For this reason, FDE-IBNP can remove both precursor and postcursor ISI, and alleviate the impact of error-propagation. Besides, our scheme has lower computational complexity than the present iterative block equalizers.

A single-carrier multiple-input multiple-output (MIMO) system with frequency-selective channels suffers from the inter-symbol interference (ISI) and the co-channel interference (CCI). To eliminate both type of interference, we propose in this letter a hybrid two-stage decision-feedback equalizer (HTS-DFE), which performs the frequency-domain equalization (FDE) in the first stage and the layered serial interference-cancellation (SIC) in the second stage. Since the decision-feedback (DF) or noise-prediction (NP) architecture can be employed in FDE or SIC, the proposed equalizer actually can have four variations that achieve the same mean square error (MSE) under the assumption of perfect feedback. Further, we combine HTS-DFE with the decoded decision-feedback (DDF) scheme to mitigate the error-propagation encountered in the practice. Simulation results confirm that the proposed HTS-DFE can outperform the existing equalizers significantly.

In orthogonal frequency-division multiplex access (OFDMA) uplink, the carrier-frequency offsets (CFOs) between the multiple transmitters and the receiver introduce inter-carrier interference (ICI) and severely degrade the performance. In this paper, based on the perfect estimation of each user's CFO, we propose two low-complexity iterative algorithms to cancel ICI due to CFOs, which are denoted as the basic algorithm and the improved algorithm with decision-feedback equalization (DFE), respectively. For the basic one, two theorems are proposed that yield a sufficient condition for the convergence of iterations. Moreover, the interference-power-evolution (IPE) charts are proposed to evaluate the convergence behavior of this interference cancellation algorithm. Motivated by the IPE chart, the procedure of DFE is introduced into the iterations, which is the basic idea of the improved algorithm. For this improved algorithm, the error-propagation effect are analyzed and suppressed by an efficient stopping criterion. From IPE charts and simulation results, it can be easily observed that the basic algorithm has the same capability of ICI cancellation as the linear optimal minimum mean square error (MMSE) method, but offers lower complexity, while the improved algorithm with DFE outperforms the MMSE method in terms of the bit-error rate (BER) performance.

The performance of decision-feedback equalization combined with maximum-likelihood detection (DFE/ML) using the fixed-delay-tree-search/decision feedback (FDTS/DF) algorithm was estimated analytically in terms of the length of the feedback-filter and the depth of the ML-detector. Performance degradation due to error propagation in the feedback-loop and in the ML-detector was taken into account by using a Markov process analysis. It was quantitatively shown that signal-to-noise-ratio (SNR) performance in high-density magnetic recording channels can be improved by combining an ML-detector with a feedback-filter and that the error propagation in the DFE channel can be reduced by using an ML-detector. Finally, it was found that near-optimum performance with regard to channel SNR and error propagation can be achieved, over the channel density range from 2 to 3, by increasing the sum of the feedback-filter length and the ML-detector depth to six bits.