Apriana Toding

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In this article, we study the optimal structure of the source precoding matrix and the relay amplifying matrices for multiple-input multiple-output (MIMO) relay communication systems with parallel relay nodes. Two types of receivers are considered at the destination node: (1) The linear minimal mean-squared error (MMSE) receiver; (2) The nonlinear decision(More)
In this paper, we study the optimal structure of the source precoding matrix and the relay amplifying matrices for multiple-input multiple-output (MIMO) relay communication systems with parallel relay nodes. We show that both the optimal source precoding matrix and the optimal relay amplifying matrices have a beamforming structure. Using the optimal(More)
In this paper, we study the optimal structure of the source precoding matrix and the relay amplifying matrices for multiple-input multiple-output (MIMO) relay communication systems with parallel relay nodes. In particular, a nonlinear decision feedback equalizer (DFE) is used at the destination node, and the minimal mean-squared error (MMSE) criterion is(More)
In this paper, we develop the optimal source precoding matrix and relay amplifying matrices for non-regenerative multiple-input multiple-output (MIMO) relay communication systems with parallel relay nodes using the projected gradient (PG) approach. We show that the optimal relay amplifying matrices have a beamforming structure. Exploiting the structure of(More)
In this paper, we develop the optimal source precoding matrix and relay amplifying matrices for non-regenerative multiple-input multiple-output (MIMO) relay communication systems with parallel relay nodes using the projected gradient (PG) approach. We show that the optimal relay amplifying matrices have a beamforming structure. Exploiting the structure of(More)
In this paper, we develop the optimal transmit beamforming vector and the relay amplifying factors for a multipleinput multiple-output (MIMO) relay communication system with distributed relay nodes. Using the optimal beamforming vector, an iterative joint source and relay beamforming algorithm is developed to minimize the mean-squared error (MSE) of the(More)
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