The aim of this paper is to propose and evaluate multi-user iterative block decision feedback equalization (IB-DFE) schemes for the uplink of single-carrier frequency-division multiple access (SC-FDMA)-based systems. It is assumed that a set of single antenna users share the same physical channel to transmit its own information to the base station, which is equipped with an antenna array. Two space-frequency multi-user IB-DFE-based processing are considered: iterative successive interference cancellation and parallel interference cancellation. In the first approach, the equalizer vectors are computed by minimizing the mean square error (MSE) of each individual user, at each subcarrier. In the second one, the equalizer matrices are obtained by minimizing the overall MSE of all users at each subcarrier. For both cases, we propose a simple yet accurate analytical approach for obtaining the performance of the discussed receivers. The proposed schemes allow an efficient user separation, with a performance close to the one given by the matched filter bound for severely time-dispersive channels, with only a few iterations.

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The aim of this paper is to design new multiuser receivers based on the iterative block decision feedback equalization concept for MC-CDMA systems with closed-form interference alignment (IA) at the transmitted side. IA is a promising technique that allows high capacity gains in interfering channels. On the other hand, iterative frequency-domain detection receivers based on the IB-DFE concept can efficiently exploit the inherent space-frequency diversity of the MIMO MC-CDMA systems. In IA-precoded based systems the spatial streams are usually separated by using a standard linear MMSE equalizer. However, for MC-CDMA based systems, linear equalization is not the most efficient way of separating spatial streams due to the residual inter-carrier interference (ICI). Therefore, we design new non-linear iterative receiver structures to efficiently remove the aligned interference and separate the spatial streams in presence of residual ICI. Two strategies are considered: in the first one the equalizer matrices are obtained by minimizing the mean square error (MSE) of each individual data stream at each subcarrier, while in the second approach the matrices are computed by minimizing the overall MSE of all data streams at each subcarrier. We also propose an accurate analytical approach for obtaining the performance of the proposed receivers. Our schemes achieve the maximum degrees of freedom provided by the IA precoding, while allowing close-to-optimum spacediversity gain, with performance approaching the matched filter bound.