Matching pursuit-based singular vectors estimation for large MIMO beamforming

In multiple-input-multiple-output (MIMO) systems, beamforming can maximise the signal-to-noise ratio by using the principal right and left singular vectors of the channel matrix as transmit and receive beam vectors, respectively. A matching pursuit (MP)-based singular vectors estimation (SVE) scheme is proposed, referred to as MP-SVE, for beamforming transmission and detection in large MIMO systems. By judiciously exploiting the specific properties of large MIMO channel matrix, the proposed MP-SVE is able to determine the optimal beamforming vector pair while circumventing the burdensome channel estimation and singular value decomposition. The simulations verify that with the same training overhead, the proposed MP-SVE remarkably outperforms the state-of-the-art counterparts.