Robust transceiver designs for MIMO relay communication systems

Recently cooperative wireless communications have attracted considerable attention, due to their potential to provide reliable, cost effective and widearea coverage of wireless networks. In cooperative wireless communication systems, relay node can be deployed in between the source and the destination nodes to reduce the transmission power from the source to neighbouring nodes and mitigate the channel fading and shadowing effects. In this scenario, the source signals travel through two hops before they are received by the destination node. Such system is called as multiple-input multipleoutput (MIMO) relay system. In this dissertation, practical aspects of wireless channels such as channel uncertainty and channel estimation errors are considered for transceiver design problems in a non-regenerative MIMO relay system. An optimal structure of the relay precoding matrix is derived to minimize the mean-squared error (MSE) in the signal waveform estimation with the assumption that the relay knows the channel covariance information (CCI) of the relay-destination link and also the full channel state information (CSI) of the source-relay link. The proposed scheme outperforms the conventional relay algorithms in terms of both MSE and bit-error-rate (BER). Next, an iterative covariance algorithm is proposed for non-regenerative MIMO relay system with direct link. It is assumed that the full CSI of the source-relay link and CCI of the relay-destination link as well as the source-destination link are available at the relay node. In order to reduce computational complexity of the proposed iterative covariance algorithm, a suboptimal covariance algorithm is proposed. The developed iterative covariance algorithm outperforms the conventional CCI based MSE algorithms. Next, an iterative joint source and relay precoder design is proposed for a non-regenerative MIMO relay system with the assumption that the relay knows the mean and CCI of the relay-destination link and the full CSI of the source-relay link. In order to reduce computational complexity of the proposed iterative design algorithm, a suboptimal relay-only precoder design algorithm is proposed. The performance of the proposed iterative joint source and relay precoder design algorithm is very close to that of the algorithm using the full CSI. Next, Tomlinson-Harashima (TH) precoder based non-linear transceiver design is proposed for a non-regenerative MIMO relay system, it is assumed that the CCI of the relay-destination link is available at the relay node. First, the structure of the optimal TH precoding matrix and the source precoding matrix is derived. Then an iterative algorithm is developed to optimize the relay precoding matrix. To reduce the computational complexity of the iterative algorithm, a simplified precoding matrices design algorithm is proposed. The proposed precoding matrices design algorithms outperform the existing algorithms. Finally, the transceiver design is investigated for a non-regenerative multicasting MIMO relay system, where one transmitter broadcasts common message to multiple receivers with the aid of a relay node. The transmitter, relay, and receivers are equipped with multiple antennas. It is assumed that the true (unknown) channel matrices have Gaussian distribution, the estimated channels are the mean value of this distribution. The channel estimation errors follow the well-known Kronecker model. Two robust transceiver design algorithms are proposed to jointly design the transmitter, relay, and receiver matrices to minimize the maximal MSE of the signal waveform estimation among all receivers. In particular, it is proved that the MSE at each receiver can be decomposed into the sum of the MSEs of the first-hop and second-hop channels. Based on this MSE decomposition, transceiver design algorithms are developed with low computational complexity. Numerical simulations demonstrate the improved robustness of the proposed transceiver design algorithm against the mismatch between the true and estimated channels.