Research Papers - Department of Electrical and Electronic Engineering
Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/679
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Publication Embargo Maximum mutual information design for MIMO systems with imperfect channel knowledge(IEEE, 2010-09-13) Ding, M; Blostein, S. DNew 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 information between the input and the output of a MIMO channel has been previously formulated as a design criterion. However, in the previous literature, there has been no analytical expression of the optimum transmit covariance matrix for this lower-bound. Here it is shown that for the general case with channel correlation at both ends, there exists a unique and globally optimum transmit covariance matrix whose explicit expression can be conveniently determined. For the special case with transmit correlation only, the closed-form optimum transmit covariance matrix is presented. Interestingly, the optimal transmitters for the maximum mutual information design and the minimum total mean-square error design share the same structure, as they do in the case with perfect channel state information. Simulation results are provided to demonstrate the effects of channel estimation errors and channel correlation on the mutual information.Publication Embargo MIMO minimum total MSE transceiver design with imperfect CSI at both ends(IEEE, 2008-10-31) Ding, M; Blostein, S. DThis 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 precoder and decoder are derived. Compared to the case with perfect channel state information (CSI), linear filters are added at both ends to balance the suppression of channel noise and the noise from imperfect channel estimation. The impact of channel estimation error as well as channel correlation on system performance is assessed, based on analytical and simulation results.