A new scheduling algorithm with low complexity for multiuser multiple-input multiple-output downlink system

Abstract

A new scheduling algorithm with low complexity for user selection is proposed for a multiuser multiple-input and multiple-output (MU-MIMO) downlink system based on block diagonalization (BD) precoding. The new algorithm provides equivalent system performance evaluated as sum-rate capacity in comparison with other user selection algorithms, such as semiorthogonal user selection (SUS) and capacity-based user selection algorithms. The proposed algorithm has the advantage of reduced computational complexity achieved by using a new volume-based user selection method that uses the product of the diagonal elements in the upper-triangular matrix obtained via Householder reduction procedure of QR factorization to the selected users channel matrix. The computational effort of the proposed algorithm is reduced by 1/3 compared with SUS algorithm. Compared with the capacity-based algorithm, the proposed algorithm does not need to perform the singular value decomposition (SVD) operation and water filling algorithm during each user selection step and hence significantly reduces the computational time. We provide numerical results of our new algorithm to confirm the sum-rate performance with the reduced complexity.