Apriana Toding

Learn 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 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. 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 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 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)
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)
  • 1