A Tutorial on the Optimization of Amplify-and-Forward MIMO Relay Systems

The remarkable promise of multiple-input multiple-output (MIMO) wireless channels has motivated an intense research activity to characterize the theoretical and practical issues associated with the design of transmit (source) and receive (destination) processing matrices under different operating conditions. This activity was primarily focused on point-to-point (single-hop) communications but more recently there has been an extensive work on two-hop or multi-hop settings in which single or multiple relays are used to deliver the information from the source to the destination. The aim of this tutorial is to provide an up-to-date overview of the fundamental results and practical implementation issues of designing amplify-and-forward MIMO relay systems

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

Joint Transceiver Optimization for Multiuser MIMO Relay Communication Systems

In this paper, we address the optimal source, relay, and receive matrices design for linear non-regenerative uplink multiuser multiple-input multiple-output (MIMO) relay communication systems. The minimum mean-squared error (MMSE) of the signal waveform estimation at the destination node is adopted as our design criterion. We develop two iterative methods to solve the highly nonconvex joint source, relay, and receiver optimization problem. In particular, we show that for given source precoding matrices, the optimal relay amplifying matrix diagonalizes the source-relay-destination channel. While for fixed relay matrix and source matrices of all other users, the source matrix of each user has a general beamforming structure. Simulation results demonstrate that the proposed iterative source and relay optimization algorithms perform much better than existing techniques in terms of both MSE and bit-error-rate

Joint Source and Relay Optimization for Multiuser MIMO Relay Communication Systems

In this paper, we design the source precoding matrices and the relay amplifying matrix of an amplify-andforward multiuser multiple-input multiple-output (MIMO) relay communication system. The minimum mean-squared error (MSE) is taken as the design criterion. We propose an alternating technique to efficiently solve the nonconvex source and relay optimization problem. It is shown that both the optimal source and relay matrices have a beamforming structure. Simulation results demonstrate that the proposed source and relay design algorithms perform much better than the existing techniques in terms of both MSE and bit-error-rate

Maximizing the Sum Rate in Cellular Networks Using Multi-Convex Optimization

In this paper, we propose a novel algorithm to maximize the sum rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise considering the signal-to-interference-plus-noise-ratio. It is known that the problem of adapting the transmit and receive filters of the users to maximize the sum rate with a sum transmit power constraint is non-convex. Our novel approach is to formulate the sum rate maximization problem as an equivalent multi-convex optimization problem by adding two sets of auxiliary variables. An iterative algorithm which alternatingly adjusts the system variables and the auxiliary variables is proposed to solve the multi-convex optimization problem. The proposed algorithm is applied to a downlink cellular scenario consisting of several cells each of which contains a base station serving several mobile stations. We examine the two cases, with or without several half-duplex amplify-and-forward relays assisting the transmission. A sum power constraint at the base stations and a sum power constraint at the relays are assumed. Finally, we show that the proposed multi-convex formulation of the sum rate maximization problem is applicable to many other wireless systems in which the estimated data symbols are multi-affine functions of the system variables.Comment: 24 pages, 5 figure