Title :
Low-Complexity Lattice Reduction-Aided Regularized Block Diagonalization for MU-MIMO Systems
Author :
Zu, Keke ; de Lamare, Rodrigo C.
Author_Institution :
Dept. of Electron., Univ. of York, York, UK
fDate :
6/1/2012 12:00:00 AM
Abstract :
By employing the regularized block diagonalization (RBD) preprocessing technique, the MU-MIMO broadcast channel is decomposed into multiple parallel independent 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 letter, 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, substantial bit error rate (BER) performance gains and a simplified receiver structure, while requiring a lower complexity.
Keywords :
MIMO communication; broadcast channels; computational complexity; diversity reception; error statistics; multi-access systems; radio receivers; singular value decomposition; BER performance; MU-MIMO broadcast channel; MU-MIMO systems; QR decomposition; RBD preprocessing technique; SVD operations; bit error rate performance; computational complexity; high data rates; low-complexity lattice reduction-aided RBD; low-complexity lattice reduction-aided regularized block diagonalization; multiple parallel independent SU-MIMO channels; orthogonalization procedure; regularized block diagonalization preprocessing technique; singular value decomposition; Bit error rate; Computational complexity; Lattices; MIMO; Matrix decomposition; Nickel; MU-MIMO; low-complexity; regularized block diagonalization (RBD);
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2012.041112.112185