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A decision feedback equalizer (DFE) utilizes the previous detector's assessment to get rid of the inter-symbol interference (ISI) on the received symbols. It is well analyzed in the literature that the DFE performs better than the linear equalizer when the ISI is sever because of its inherent nonlinear nature. Equalization of wireless multiple-input multiple-output (MIMO) frequency-selective channels is a challenging task mainly due to the fact that the respective MIMO equalizers should cope with inter-symbol, as well as inter-stream interference. Different techniques have been proposed for MIMO DFE. In this paper we have developed a constrained MIMO DFE for CDMA system based on constrained optimization. This is achieved by minimizing the conventional mean-square-error criterion subject to the variance of the multiple-access interference (MAI) plus noise. The novelty of the work resides in the fact that such a constrained optimization has never been employed in the design of MIMO DFE. The proposed MIMO DFE algorithm is tested in different fading environments and its performance is compared with that of the conventional least mean-square (LMS) and normalized LMS (NLMS) algorithms. Simulation results show that the proposed constrained MIMO DFE outperforms the conventional MIMO DFEs based on LMS and NLMS algorithms.