Superimposed Training Designs for Spatially Correlated MIMO-OFDM Systems

Only one asymptotic training design for a special case of channel correlation was proposed in the literature for spatially correlated Multiple-Input Multiple-Output with Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) systems. To fill this gap, this paper applies tractable Semi-Definite Programming (SDP) to obtain the optimal superimposed training signals for the general case of channel correlation. For a more efficient computation, two approximate designs are also proposed. Simulation results demonstrate the efficiency of the authors' approach and its advantage over the asymptotic design.