Precoder Optimization for Nonlinear MIMO Transceiver Based on Arbitrary Cost Function

— Assuming full channel state information (CSI) at both transmitter (CSIT) and receiver (CSIR), we consider optimizing a nonlinear MIMO transceiver with (nonlinear) decision feedback equalizer (DFE) with respect to some global cost function f0. Setting the receiver to be a minimum meansquared error (MMSE) DFE, the MIMO transceiver optimization problem reduces to optimizing a linear precoder. Based on the generalized triangular decomposition (GTD) and majorization theory, we prove that for any cost function f0 the optimum precoder is of the same special structure and hence the original complicated matrix optimization problem can be significantly simplified to an optimization problem with scalar-valued variables. Furthermore, if the cost function is specialized to the cases where the composite function f0 ◦ exp is either Schur-convex or Schur-concave, then the nonlinear transceiver design becomes exceedingly simple. In particular, when f0 ◦ exp is Schur-convex, the optimum nonlin...

• Type: Conference
• Year: 2007
• Where: CISS
• Authors: Yi Jiang, Daniel Pérez Palomar, Mahesh K. Varanasi
• Keywords: CISS 2007, Cost Function, MIMO Transceiver, Nonlinear Transceiver Design