Error-entropy based channel state estimation of spatially correlated MIMO-OFDM

This paper deals with optimized training sequences to estimate multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) channel states in the presence of spatial fading correlations. The optimization criterion is the entropy minimization of the error between the high multi-dimensional and correlated channel state and its estimator. The globally optimized training sequences are exactly solved by a semi-definite programming (SDP) of tractable computational complexity O((Mt(Mt + 1)/2)^2.5), where Mt is the transmit antenna number. With new tight two-sided bounds for the objective function, the optimal value of the generic SDP can be approximately solved by the standard water-filling algorithm. Intensive simulation results are provided to illustrate the performance of our methods.