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

Wireless MIMO Switching: Weighted Sum Mean Square Error and Sum Rate Optimization

This paper addresses joint transceiver and relay design for a wireless multiple-input-multiple-output (MIMO) switching scheme that enables data exchange among multiple users. Here, a multi-antenna relay linearly precodes the received (uplink) signals from multiple users before forwarding the signal in the downlink, where the purpose of precoding is to let each user receive its desired signal with interference from other users suppressed. The problem of optimizing the precoder based on various design criteria is typically non-convex and difficult to solve. The main contribution of this paper is a unified approach to solve the weighted sum mean square error (MSE) minimization and weighted sum rate maximization problems in MIMO switching. Specifically, an iterative algorithm is proposed for jointly optimizing the relay's precoder and the users' receive filters to minimize the weighted sum MSE. It is also shown that the weighted sum rate maximization problem can be reformulated as an iterated weighted sum MSE minimization problem and can therefore be solved similarly to the case of weighted sum MSE minimization. With properly chosen initial values, the proposed iterative algorithms are asymptotically optimal in both high and low signal-to-noise ratio (SNR) regimes for MIMO switching, either with or without self-interference cancellation (a.k.a., physical-layer network coding). Numerical results show that the optimized MIMO switching scheme based on the proposed algorithms significantly outperforms existing approaches in the literature.Comment: This manuscript is under 2nd review of IEEE Transactions on Information Theor

Robust MMSE beamforming for multiantenna relay networks

In this paper, we propose a robust minimum mean square error (MMSE) based beamforming technique for multiantenna relay broadcast channels, where a multi-antenna base station transmits signal to single antenna users with the help of a multiantenna relay. The signal transmission from the base station to the single antenna users is completed in two time slots, where the relay receives the signal from the base station in the first time slot and it then forwards the received signal to different users based on amplify and forward protocol. We propose a robust beamforming technique for sum-power minimization problem with imperfect channel state information (CSI) between the relay and the users. This robust scheme is developed based on the worst-case optimization framework and Nemirovski Lemma by incorporating uncertainties in the CSI. The original optimization problem is divided into three subproblems due to joint non-convexity in terms of beamforming vectors at the base station, the relay amplification matrix, and receiver coefficients. These subproblems are formulated into a convex optimization framework by exploiting Nemirovski Lemma, and an iterative algorithm is developed by alternatively optimizing each of them with channel uncertainties. In addition, we provide an optimization framework to evaluate the achievable worst-case mean square error (MSE) of each user for a given set of design parameters. Simulation results have been provided to validate the convergence of the proposed algorithm

Linear Precoding Designs for Amplify-and-Forward Multiuser Two-Way Relay Systems

Two-way relaying can improve spectral efficiency in two-user cooperative communications. It also has great potential in multiuser systems. A major problem of designing a multiuser two-way relay system (MU-TWRS) is transceiver or precoding design to suppress co-channel interference. This paper aims to study linear precoding designs for a cellular MU-TWRS where a multi-antenna base station (BS) conducts bi-directional communications with multiple mobile stations (MSs) via a multi-antenna relay station (RS) with amplify-and-forward relay strategy. The design goal is to optimize uplink performance, including total mean-square error (Total-MSE) and sum rate, while maintaining individual signal-to-interference-plus-noise ratio (SINR) requirement for downlink signals. We show that the BS precoding design with the RS precoder fixed can be converted to a standard second order cone programming (SOCP) and the optimal solution is obtained efficiently. The RS precoding design with the BS precoder fixed, on the other hand, is non-convex and we present an iterative algorithm to find a local optimal solution. Then, the joint BS-RS precoding is obtained by solving the BS precoding and the RS precoding alternately. Comprehensive simulation is conducted to demonstrate the effectiveness of the proposed precoding designs.Comment: 13 pages, 12 figures, Accepted by IEEE TW

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.