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This paper presents new results on joint linear transceiver design under the minimum total mean-square error (MSE) criterion, with channel mean as well as both transmit and receive correlation information at both ends of a multiple-input multiple-output (MIMO) link. The joint design is formulated into an optimization problem. The optimum closed-form(More)
Joint linear minimum sum mean-squared error (referred to as MSMSE) transmitter and receiver (transceiver) optimization problems are formulated for multiuser MIMO systems under a sum power constraint assuming imperfect channel state information (CSI). Both the uplink and the dual downlink are considered. Based on the Karush-Kuhn-Tucker (KKT) conditions(More)
New results on maximum mutual information design for multiple-input multiple-output (MIMO) systems are presented, assuming that both transmitter and receiver know only an estimate of the channel state as well as the transmit and receive correlation. Since an exact capacity expression is difficult to obtain for this case, a tight lower-bound on the mutual(More)
In this paper, a rate-adaptive spatial multiplexing system with zero-forcing (ZF) detection is proposed for spatially-white MIMO Rayleigh fading channels, feeding back only constellation selection information, which has the advantage of low feedback compared to classical approaches. We evaluate the spectral efficiency achieved by rate adaptation according(More)
— This paper presents a new result on minimum total mean squared error (MSE) joint transceiver design for multiple-input multiple-output (MIMO) systems, with imperfect channel state information (CSI) at both ends and subject to a total power constraint. The channel knowledge here is the channel mean and transmit correlation information. The joint design is(More)
— Duality between the multi-antenna multiuser up-link and the downlink has been discovered in terms of sum rate, capacity region, signal-to-interference-plus-noise-ratio (SINR) region or normalized mean-squared error (MSE) region. Previous work on duality has assumed perfect channel knowledge. However , channel estimation is never perfect in practice. In(More)
— In this paper, a joint linear minimum sum mean-squared error transceiver optimization problem is formulated for multiuser MIMO uplink systems under a sum power constraint assuming imperfect channel state information (CSI). Two methods are proposed to solve this problem. One is based on the associated Karush-Kuhn-Tucker conditions. The other is to solve an(More)