Efficient multi-user MIMO precoding based on GSVD and vector perturbation

We present an efficient precoding method by using generalized singular value decomposition (GSVD) and vector perturbation in the downlink of multi-user MIMO. Linear precoding/decoding matrices are explicitly computed through the GSVD algorithm, avoiding any matrix inversion or squaring operation. Accordingly, the computational complexity can be drastically reduced compared to the conventional iterative algorithms. In addition, by considering the inter-user interference, we derive a new perturbation vector that minimizes system-wide mean-squared-error of detected symbols. We also show that the proposed precoding scheme is suitable to update the precoding weights efficiently when the channel is newly updated, rather than recomputing the precoding weights for all users from scratch. ► An efficient precoding is proposed based on GSVD and vector perturbation. ► Precoding matrices are computed without any matrix inversion or squaring operation. ► The proposed precoding requires much less flops than the earlier methods. ► The proposed precoding is suitable to update the precoding weights efficiently.