Abstract

In this paper we present a novel way of jointly estimating the coupling matrix of closely spaced receive antennas as well as the spatial channel of compact MIMO systems. Unlike conventional approaches, we do not assume any knowledge of the types and geometries of the antennas, or their separations, or having line of sight spatial channels. Our algorithm is based only on changing the load impedances of the antennas and measuring the voltages across such loads. We use the nonlinear relation between the load impedances and the compound channel estimates in order to estimate both the spatial channel and the coupling matrix. Our algorithm is of relevance to future communication systems incorporating heterogeneous networks in dense environments. In such networks different users/nodes may occasionally be closely spaced and hence, mutually coupled. Using our algorithm, they can estimate both the coupling matrix and the spatial channel matrix in real-time and thereby optimize their matching networks and signal processing in order to enhance their performance.

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