Research Papers - Department of Electrical and Electronic Engineering

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/679

Browse

Filters

2007 - 20092

Advanced Search

Filter by

Settings

Subject: search.filters.subject.Transceiver Design

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationEmbargo
    A general framework for MIMO transceiver design with imperfect CSI and transmit correlation
    (IEEE, 2009-09-13) Ding, M; Blostein, S. D; Mow, W. H; Siriteanu, C
    Assuming perfect channel state information (CSI), linear precoding/decoding for multiple-input multiple-output (MIMO) systems has been considered in the literature under various performance criteria, such as minimum total mean-square error (MSE), maximum mutual information, and minimum average bit error rate (BER). It has been shown that these criteria belong to a set of reasonable Schur-concave or Schur-convex objective functions of the diagonal entries of the system mean-square error (MSE) matrix. In this paper, assuming only the knowledge of channel mean and transmit correlation at both ends, a general theoretical framework is presented to derive the optimum precoder and decoder for MIMO systems using these objective functions. It is shown that for all these objective functions the optimum transceivers share a similar structure. Compared to the case with perfect CSI, a linear filter is added to both ends to balance the suppression of channel noise and the additional noise induced from channel estimation error. Simulation results are provided.
  • Thumbnail Image
    PublicationEmbargo
    MIMO LMMSE transceiver design with imperfect CSI at both ends
    (IEEE, 2007-06-24) Blostein, S. D; Ding, M
    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 formulated into an optimization problem, to which the closed-form optimum solution is found. The optimum precoder consists of a linear filter, a matrix which collects effective channel eigenmodes, and a diagonal power allocation matrix. The linear filter balances the suppression of channel noise and the additional noise induced by channel estimation error. Given the precoder, the optimum decoder is simply a linear minimum MSE (LMMSE) data estimator. The performance degradations due to imperfect channel estimation and/or transmit correlation are demonstrated by simulation results. The relation between the minimum total MSE design and the maximum mutual information design is determined as well, under the above mentioned imperfect CSI.