Near-Optimum Vector Perturbation Precoding Using a Candidate List

Abstract

An improvement to lattice-reduction-aided (LRA) vector perturbation precoding for multi-user MIMO downlink is introduced. Closest lattice point approximation by means of lattice reduction techniques can significantly lower the complexity of the closest point search compared to using a sphere encoder, but the performance of the system is also impaired. In this paper, we propose a new technique improving the suboptimal LRA closest-point approximation in a subsequent stage. This stage consists of a low-complexity candidate list generation of also likely approximations, and an evaluation step of this list. We present simulation results showing that our improvement to the LRA closest-point approximation can achieve near-optimum performance.