Open AccessSimplified QR‐decomposition based and lattice reduction‐assisted multi‐user multiple‐input–multiple‐output precoding scheme
Author(s) -
Fang Shu,
Wu Jian,
Lu Chengyi,
Yue Zongdi,
Han Yuanchao
Publication year - 2016
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2015.0643
Subject(s) - precoding , mimo , qr decomposition , lattice reduction , computational complexity theory , zero forcing precoding , computer science , algorithm , multi user mimo , matrix decomposition , mathematics , electronic engineering , telecommunications , engineering , eigenvalues and eigenvectors , channel (broadcasting) , physics , quantum mechanics
Future wireless communication systems require more and more antennas at the transceiver to improve the achievable rates. Multi‐user multiple‐input multiple‐output (MU‐MIMO) technique is regarded as a potential technique to serve large number of users simultaneously to further increase the achievable rates in MIMO systems. If the number of antennas at the transceiver is large, the computational complexity of precoding becomes the bottleneck and a big challenge in MU‐MIMO system. In this paper, a simplified QR decomposition with lattice reduction assisted MU‐MIMO precoding scheme named S‐QR‐LR is proposed as a low‐complexity MU‐MIMO transmission scheme. The simplified QR decomposition method is delicately designed and operated twice for the proposed precoding scheme not only to achieve good performance but also reduce the computational complexity significantly. The proposed S‐QR‐LR scheme first uses the simplified QR decomposition operation to balance the multi‐user interference and the noise. Then, the proposed S‐QR‐LR precoding scheme utilizes the simplified QR decomposition method again with the assist of lattice reduction to obtain the precoding gain to further improve the performance with low computational complexity. Analytical and simulation results show that the proposed S‐QR‐LR precoding scheme achieves best performance among the existing precoding schemes, but requires the lowest computational complexity.