The problem of stochastically robust minimum
mean square error (MMSE) transceiver design is addressed for
multiple-input multiple-output (MIMO) point-to-point channels
with different imperfect channel state information (CSI) at the
receiver and the transmitter. While the receiver has distribution
knowledge of the doubly correlated Gaussian channel that is
conditioned on pilot-based training observations (partial CSIRx),
the transmitter has either conditional distribution knowledge
about the receiver’s observations based on feedback (partial
CSITx), or only unconditioned distribution knowledge (statistical
CSITx). In case of partial CSITx, the design is based on an
alternating optimization of the transmit and receive filter. For
statistical CSITx, a novel closed-form expression for the expected
MMSE is calculated and the structure of the optimal precoder
is determined. This enables us to employ an efficient gradient
projection method for the robust precoder design.
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The problem of stochastically robust minimum
mean square error (MMSE) transceiver design is addressed for
multiple-input multiple-output (MIMO) point-to-point channels
with different imperfect channel state information (CSI) at the
receiver and the transmitter. While the receiver has distribution
knowledge of the doubly correlated Gaussian channel that is
conditioned on pilot-based training observations (partial CSIRx),
the transmitter has either conditional distribution knowledge
about...
»