LAUSR

A method for reconstructing multiple-input multiple-output (MIMO) channel correlation matrices from lower dimensional channel measurements is presented. Exploiting the symmetry of correlation matrix structure enables reproducing higher dimensional MIMO channel matrices from available lower order measurements. This leads to practically important applications allowing prediction of higher dimensional MIMO system capacity. In particular, we study Kronecker-type MIMO channels suitable for reconstructing full channel matrices from partial information about transmit-receive fading in spatial and polarimetric domains and analyze validity conditions for such models. One of the important channel conditions is Doppler frequency related to non-stationarity in the environment. We present simulations of cluster-type scattering model using $$2\times 2$$2×2 MIMO channel correlation matrices to predict performance of $$2\times 4$$2×4 MIMO system including recovery of angular power spectrum. An example of dual circular polarized $$2\times 4$$2×4 MIMO land mobile satellite measurements in 2.5 GHz frequency band illustrates applicability of the method to reconstruct spatial and polarimetric channel correlation matrices for estimating ergodic channel capacity from single-antenna or uni-polarized measurements.