Quantization Error Correction Schemes for Lattice-Reduction Aided MIMO Detectors

Abstract

Lattice reduction aided (LRA) linear detectors have been known to achieve near optimal performance at low complexity. However, one weakness of LRA detector is that the quantization step in LRA detector is not optimal. Based on simulation results, we show that most of detection errors in LRA linear detectors are due to quantization errors. We then propose two methods to correct the quantization errors. In the first method, sphere detectors are introduced to correct quantization errors at low additional complexity. As a second approach, we propose a list quantization scheme which can generate a list of candidate symbols from the original LRA estimated symbols. From these listed symbols, decisions are made according to the minimum Euclidean distance between the received and estimated points. It is shown by simulations that both methods provide significant BER performance improvements with only a small additional complexity.