Robust Joint Precoder and Equalizer Design in MIMO Communication Systems

We address joint design of robust precoder and equalizer in a MIMO communication system using the minimization of weighted sum of mean square errors. In addition to imperfect knowledge of channel state information, we also account for inaccurate awareness of interference plus noise covariance matrix and power shaping matrix. We follow the worst-case model for imperfect knowledge of these matrices. First, we derive the worst-case values of these matrices. Then, we transform the joint precoder and equalizer optimization problem into a convex scalar optimization problem. Further, the solution to this problem will be simplified to a depressed quartic equation, the closed-form expressions for roots of which are known. Finally, we propose an iterative algorithm to obtain the worst-case robust transceivers.Comment: 2 figures, 5 pages, conferenc

Robust Beamforming for Amplify-and-Forward MIMO Relay Systems Based on Quadratic Matrix Programming

In this paper, robust transceiver design based on minimum-mean-square-error (MMSE) criterion for dual-hop amplify-and-forward MIMO relay systems is investigated. The channel estimation errors are modeled as Gaussian random variables, and then the effect are incorporated into the robust transceiver based on the Bayesian framework. An iterative algorithm is proposed to jointly design the precoder at the source, the forward matrix at the relay and the equalizer at the destination, and the joint design problem can be efficiently solved by quadratic matrix programming (QMP).Comment: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'2010), U.S.

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

Robust joint design of linear relay precoder and destination equalizer for dual-hop amplify-and-forward MIMO relay systems

This paper addresses the problem of robust linear relay precoder and destination equalizer design for a dual-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay system, with Gaussian random channel uncertainties in both hops. By taking the channel uncertainties into account, two robust design algorithms are proposed to minimize the mean-square error (MSE) of the output signal at the destination. One is an iterative algorithm with its convergence proved analytically. The other is an approximated closed-form solution with much lower complexity than the iterative algorithm. Although the closed-form solution involves a minor relaxation for the general case, when the column covariance matrix of the channel estimation error at the second hop is proportional to identity matrix, no relaxation is needed and the proposed closed-form solution is the optimal solution. Simulation results show that the proposed algorithms reduce the sensitivity of the AF MIMO relay systems to channel estimation errors, and perform better than the algorithm using estimated channels only. Furthermore, the closed-form solution provides a comparable performance to that of the iterative algorithm. © 2006 IEEE.published_or_final_versio

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

Joint optimization of transceivers with fractionally spaced equalizers

In this paper we propose a method for joint optimization of transceivers with fractionally spaced equalization (FSE). We use the effective single-input multiple-output (SIMO) model for the fractionally spaced receiver. Since the FSE is used at the receiver, the optimized precoding scheme should be changed correspondingly. Simulation shows that the proposed method demonstrates remarkable improvement for jointly optimal linear transceivers as well as transceivers with decision feedback

Joint robust weighted LMMSE transceiver design for dual-hop AF multiple-antenna relay systems

In this paper, joint transceiver design for dual-hop amplify-and-forward (AF) MIMO relay systems with Gaussian distributed channel estimation errors in both two hops is investigated. Due to the fact that various linear transceiver designs can be transformed to a weighted linear minimum mean-square-error (LMMSE) transceiver design with specific weighting matrices, weighted mean square error (MSE) is chosen as the performance metric. Precoder matrix at source, forwarding matrix at relay and equalizer matrix at destination are jointly designed with channel estimation errors taken care of by Bayesian philosophy. Several existing algorithms are found to be special cases of the proposed solution. The performance advantage of the proposed robust design is demonstrated by the simulation results. © 2011 IEEE.published_or_final_versionThe 2011 IEEE Global Telecommunications Conference (GLOBECOM 2011), Beijing, China, 5-9 December 2011. In Globecom. IEEE Conference and Exhibition, 2011, p. 1-