Apriana Toding

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—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 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 zero-forcing (ZF) and minimum mean-squared error (MMSE) algorithms for a multiple-input multiple-output (MIMO) relay network and compare their performance in terms of bit-error-rate (BER). In particular, we investigate their performance with and without using the successive interference cancellation (SIC) at the receiver. Our(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 precod-ing 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 beam-forming vector and the relay amplifying factors for a multiple-input 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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