Tensor-based approach to channel estimation in amplify-and-forward MIMO relaying systems

A novel method is devised to jointly estimate the channel matrices involved in a relay-assisted MIMO communication system. We first propose a trilinear coding structure to be used at the amplify-and-forward (AF) relays for combining the received signals while spreading the combined signals across transmit antennas and time blocks, before retransmission. This structure provides antenna selection at the relays and different amplification schemes with non-diagonal amplification matrices. Then, by exploiting the tensor structure of the end-to-end MIMO links, the channel matrices are iteratively estimated by means of a combined alternating least squares (Comb-ALS-MIMO) algorithm that couples PARAFAC and Tucker2 decompositions for the received signals. The proposed method provides an effective solution to the channel estimation problem due to the efficient use of cooperative diversity and tensor-based signal processing.