Multicasting MIMO Relay Optimization Based on Min-Max MSE Criterion

In this paper, we consider a multicasting multiple-input multiple-output (MIMO) relay system where the transmitter multicasts a common message to multiple receivers with the aid of a relay node, all equipped with multiple antennas. Given the power constraints at the source and the relay nodes, we aim at minimizing the maximal mean-squared error (MSE) of the signal waveform estimation among the destination nodes through joint source, relay, and receiver matrices optimization. We provide a low complexity solution to this highly nonconvex optimization problem. In particular, we show that under the (moderately) high signal-to-noise ratio (SNR) assumption, the joint source and relay optimization problem can be solved using standard semidefinite programming (SDP) technique. Numerical simulations provided demonstrate the effectiveness of the proposed algorithm

Robust transceiver designs for MIMO relay communication systems

The thesis investigates robust linear and non-linear transceiver design problems for wireless MIMO relay communication systems with the assumption that the partial information of the channel is available at the relay node. The joint source and relay optimization problems for MIMO relay systems are highly nonconvex, in general. We transform the problems into suitable forms which can be efficiently solved using standard convex optimization techniques. The proposed design schemes outperform the existing techniques

Precoding design for MIMO relay multicasting

In this paper, we consider a two-hop multicasting multiple-input multiple-output (MIMO) relay system where one transmitter multicasts common message to multiple receivers with the aid of a relay node, and all nodes are equipped with multiple antennas. Joint transmit and relay precoding design problems are investigated for multicasting multiple data streams based on two design criteria. In the first scheme, we aim at minimizing the maximal mean-squared error (MSE) of the signal waveform estimation among all receivers subjecting to power constraints at the transmitter and the relay node. This problem is highly nonconvex with matrix variables and the exactly optimal solution is very hard to obtain. We develop an iterative algorithm to jointly optimize the transmitter, relay, and receiver matrices through solving convex subproblems. By exploiting the optimal structure of the relay precoding matrix, we then propose a low complexity solution which decouples the optimization of the transmitter and relay matrices under the (moderately) high first-hop signal-to-noise ratio (SNR) assumption. In the second scheme, we propose a total transmission power minimization strategy subjecting to quality-of-service (QoS) constraints. By using the optimal structure of the relay precoding matrix and the (moderately) high first-hop SNR assumption, we show that this problem can be solved using the semidefinite programming (SDP) technique. Numerical simulations demonstrate the effectiveness of the proposed algorithms. Interestingly, we show that for the special case of single data stream multicasting, the relay precoding matrix optimization problem can be equivalently converted to the transmit beamforming problem for single-hop multicasting systems

Joint source and relay optimization for interference MIMO relay networks

This paper considers multiple-input multiple-output (MIMO) relay communication in multi-cellular (interference) systems in which MIMO source-destination pairs communicate simultaneously. It is assumed that due to severe attenuation and/or shadowing effects, communication links can be established only with the aid of a relay node. The aim is to minimize the maximal mean-square-error (MSE) among all the receiving nodes under constrained source and relay transmit powers. Both one- and two-way amplify-and-forward (AF) relaying mechanisms are considered. Since the exactly optimal solution for this practically appealing problem is intractable, we first propose optimizing the source, relay, and receiver matrices in an alternating fashion. Then we contrive a simplified semidefinite programming (SDP) solution based on the error covariance matrix decomposition technique, avoiding the high complexity of the iterative process. Numerical results reveal the effectiveness of the proposed schemes

Rank-Two Beamforming and Power Allocation in Multicasting Relay Networks

In this paper, we propose a novel single-group multicasting relay beamforming scheme. We assume a source that transmits common messages via multiple amplify-and-forward relays to multiple destinations. To increase the number of degrees of freedom in the beamforming design, the relays process two received signals jointly and transmit the Alamouti space-time block code over two different beams. Furthermore, in contrast to the existing relay multicasting scheme of the literature, we take into account the direct links from the source to the destinations. We aim to maximize the lowest received quality-of-service by choosing the proper relay weights and the ideal distribution of the power resources in the network. To solve the corresponding optimization problem, we propose an iterative algorithm which solves sequences of convex approximations of the original non-convex optimization problem. Simulation results demonstrate significant performance improvements of the proposed methods as compared with the existing relay multicasting scheme of the literature and an algorithm based on the popular semidefinite relaxation technique

Hybrid Transceiver Optimization for Multi-Hop Communications

Multi-hop communication with the aid of large-scale antenna arrays will play a vital role in future emergence communication systems. In this paper, we investigate amplify-and-forward based and multiple-input multiple-output assisted multi-hop communication, in which all nodes employ hybrid transceivers. Moreover, channel errors are taken into account in our hybrid transceiver design. Based on the matrix-monotonic optimization framework, the optimal structures of the robust hybrid transceivers are derived. By utilizing these optimal structures, the optimizations of analog transceivers and digital transceivers can be separated without loss of optimality. This fact greatly simplifies the joint optimization of analog and digital transceivers. Since the optimization of analog transceivers under unit-modulus constraints is non-convex, a projection type algorithm is proposed for analog transceiver optimization to overcome this difficulty. Based on the derived analog transceivers, the optimal digital transceivers can then be derived using matrix-monotonic optimization. Numeral results obtained demonstrate the performance advantages of the proposed hybrid transceiver designs over other existing solutions.Comment: 32 pages, 6 figures. This manuscript has been submitted to IEEE Journal on Selected Areas in Communications (special issue on Multiple Antenna Technologies for Beyond 5G