Least-squares iterative peak-to-average ratio reduction for MIMO-OFDM systems

This manuscript addresses peak-to-average ratio (PAR) reduction in orthogonal frequency division multiplexing (OFDM) based multiple-input multiple-output (MIMO) systems. A new technique for PAR reduction in point-to-point scenarios is proposed. Singular value decomposition (SVD) algorithms usually sort the singular values of a MIMO channel in descending order. The last singular value and the associated eigenchannels of a MIMO-OFDM channel are often very weak. Not using them for data transmission will offer redundancy for PAR reduction. These eigenchannels are used to approximate the peaks which exceed a given target value in a least-squares fashion. This approximated exceedence model is then subtracted from the original signal in time domain for PAR reduction. It has been shown that a remarkable gain can be obtained with the proposed algorithm with a negligible increase in the average power and capacity loss.