Lattice reduction-aided regularized block diagonalization for multiuser MIMO systems

By employing the regularized block diagonalization (RBD) preprocessing technique, the multi-user multi-input multi-output (MU-MIMO) broadcast channel is decomposed into multiple parallel independent single user multi-input multi-output (SU-MIMO) channels and achieves the maximum diversity order at high data rates. The computational complexity of RBD, however, is relatively high due to two singular value decomposition (SVD) operations. In this paper, a low-complexity lattice reduction aided RBD is proposed. The first SVD is replaced by a QR decomposition, and the orthogonalization procedure provided by the second SVD is substituted by a lattice reduction whose complexity is mainly contributed by a QR decomposition. Simulation results show that the proposed algorithm can achieve almost the same sum-rate as RBD while offering a lower complexity and substantial BER gains with perfect as well as imperfect channel state information at the transmit side.