Low Complexity MMSE Vector Precoding Using Lattice Reduction for MIMO Systems

—In this paper, a lattice-reduction-aided (LRA) With such an approximation, the complexity of VP is greatly minimum mean square error (MMSE) vector precoding (VP) is reduced. proposed for multiple input multiple output (MIMO) systems. Three schemes are provided for the perturbation vector design In fact, the above VP schemes are zero-forcing (ZF) by Babai’s approximation procedures based on lattice reduction approaches. It is well known that noise amplification of ZF is method to reduce the complexity. Performance and complexity significant and harms the performance. On the other hand, the analysis are provided. Simulation results show that the proposed minimum mean square error (MMSE) approach offers the schemes significantly outperform the conventional MMSE optimal tradeoff between noise amplification and residual Tomlinson-Harashima precoding (THP) and the zero forcing interference in a mean square error (MSE) sense. MMSE (ZF) VP. Compared with the MMSE VP via closest-point sear...

• Type: Conference
• Year: 2007
• Where: ICC
• Authors: Feng Liu, Ling-ge Jiang, Chen He
• Keywords: Communications, ICC 2007, Lattice Reduction, Mean Square Error, Minimum Mean Square Error