Robust Transceiver Design for AF MIMO Relay Systems with Column Correlations

In this paper, we investigate the robust transceiver design for dual-hop amplify-and-forward (AF) MIMO relay systems with Gaussian distributed channel estimation errors. Aiming at maximizing the mutual information under imperfect channel state information (CSI), source precoder at source and forwarding matrix at the relay are jointly optimized. Using some elegant attributes of matrix-monotone functions, the structures of the optimal solutions are derived first. Then based on the derived structure an iterative waterfilling solution is proposed. Several existing algorithms are shown to be special cases of the proposed solution. Finally, the effectiveness of the proposed robust design is demonstrated by simulation results.Comment: 6 Pages, 1 Figur

How to Understand LMMSE Transceiver Design for MIMO Systems From Quadratic Matrix Programming

In this paper, a unified linear minimum mean-square-error (LMMSE) transceiver design framework is investigated, which is suitable for a wide range of wireless systems. The unified design is based on an elegant and powerful mathematical programming technology termed as quadratic matrix programming (QMP). Based on QMP it can be observed that for different wireless systems, there are certain common characteristics which can be exploited to design LMMSE transceivers e.g., the quadratic forms. It is also discovered that evolving from a point-to-point MIMO system to various advanced wireless systems such as multi-cell coordinated systems, multi-user MIMO systems, MIMO cognitive radio systems, amplify-and-forward MIMO relaying systems and so on, the quadratic nature is always kept and the LMMSE transceiver designs can always be carried out via iteratively solving a number of QMP problems. A comprehensive framework on how to solve QMP problems is also given. The work presented in this paper is likely to be the first shoot for the transceiver design for the future ever-changing wireless systems.Comment: 31 pages, 4 figures, Accepted by IET Communication

Matrix-Monotonic Optimization for MIMO Systems

For MIMO systems, due to the deployment of multiple antennas at both the transmitter and the receiver, the design variables e.g., precoders, equalizers, training sequences, etc. are usually matrices. It is well known that matrix operations are usually more complicated compared to their vector counterparts. In order to overcome the high complexity resulting from matrix variables, in this paper we investigate a class of elegant multi-objective optimization problems, namely matrix-monotonic optimization problems (MMOPs). In our work, various representative MIMO optimization problems are unified into a framework of matrix-monotonic optimization, which includes linear transceiver design, nonlinear transceiver design, training sequence design, radar waveform optimization, the corresponding robust design and so on as its special cases. Then exploiting the framework of matrix-monotonic optimization the optimal structures of the considered matrix variables can be derived first. Based on the optimal structure, the matrix-variate optimization problems can be greatly simplified into the ones with only vector variables. In particular, the dimension of the new vector variable is equal to the minimum number of columns and rows of the original matrix variable. Finally, we also extend our work to some more general cases with multiple matrix variables.Comment: 37 Pages, 5 figures, IEEE Transactions on Signal Processing, Final Versio

Maximum mutual information design for amplify-and-forward multi-hop MIMO relaying systems under channel uncertainties

Conference Theme: PHY and FundamentalsIn this paper, we investigate maximum mutual information design for multi-hop amplify-and-forward (AF) multiple-input multiple-out (MIMO) relaying systems with imperfect channel state information, i.e., Gaussian distributed channel estimation errors. The robust design is formulated as a matrix-variate optimization problem. Exploiting the elegant properties of Majorization theory and matrix-variate functions, the optimal structures of the forwarding matrices at the relays and precoding matrix at the source are derived. Based on the derived structures, a water-filling solution is proposed to solve the remaining unknown variables. © 2012 IEEE.published_or_final_versionThe 2012 IEEE Wireless Communications and Networking Conference (WCNC), Paris, France, 1-4 April 2012. In IEEE Wireless Communications and Networking Conference Proceedings, 2012, p. 781-78

Bayesian robust linear transceiver design for dual-hop amplify-and-forward MIMO relay systems

In this paper, we address the robust linear transceiver design for dual-hop amplify-and-forward (AF) MIMO relay systems, where both transmitters and receivers have imperfect channel state information (CSI). With the statistics of channel estimation errors in the two hops being Gaussian, we formulate the robust linear-minimum-mean-square-error (LMMSE) transceiver design problem using the Bayesian framework, and derive a closed-form solution. Simulation results show that the proposed algorithm reduces the sensitivity of the relay system to channel estimation errors, and performs better than the algorithm using estimated channel only.published_or_final_versionThe IEEE Global Telecommunications Conference (GLOBECOM 2009), Honolulu, HI., 30 November-4 December 2009. In Proceedings of GLOBECOM, 2009, p. 1-

A General Robust Linear Transceiver Design for Multi-Hop Amplify-and-Forward MIMO Relaying Systems

In this paper, linear transceiver design for multi-hop amplify-and-forward (AF) multiple-input multiple-out (MIMO) relaying systems with Gaussian distributed channel estimation errors is investigated. Commonly used transceiver design criteria including weighted mean-square-error (MSE) minimization, capacity maximization, worst-MSE/MAX-MSE minimization and weighted sum-rate maximization, are considered and unified into a single matrix-variate optimization problem. A general robust design algorithm is proposed to solve the unified problem. Specifically, by exploiting majorization theory and properties of matrix-variate functions, the optimal structure of the robust transceiver is derived when either the covariance matrix of channel estimation errors seen from the transmitter side or the corresponding covariance matrix seen from the receiver side is proportional to an identity matrix. Based on the optimal structure, the original transceiver design problems are reduced to much simpler problems with only scalar variables whose solutions are readily obtained by iterative water-filling algorithm. A number of existing transceiver design algorithms are found to be special cases of the proposed solution. The differences between our work and the existing related work are also discussed in detail. The performance advantages of the proposed robust designs are demonstrated by simulation results.Comment: 30 pages, 7 figures, Accepted by IEEE Transactions on Signal Processin

Robust Transceiver with Tomlinson-Harashima Precoding for Amplify-and-Forward MIMO Relaying Systems

In this paper, robust transceiver design with Tomlinson-Harashima precoding (THP) for multi-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying systems is investigated. At source node, THP is adopted to mitigate the spatial intersymbol interference. However, due to its nonlinear nature, THP is very sensitive to channel estimation errors. In order to reduce the effects of channel estimation errors, a joint Bayesian robust design of THP at source, linear forwarding matrices at relays and linear equalizer at destination is proposed. With novel applications of elegant characteristics of multiplicative convexity and matrix-monotone functions, the optimal structure of the nonlinear transceiver is first derived. Based on the derived structure, the transceiver design problem reduces to a much simpler one with only scalar variables which can be efficiently solved. Finally, the performance advantage of the proposed robust design over non-robust design is demonstrated by simulation results.Comment: IEEE Journal on Selected Areas in Communications - Special Issue on Theories and Methods for Advanced Wireless Relays The final version and several typos have been correcte