Practical aspects of preprocessing techniques for K-Best tree search MIMO detectors

Abstract

It has been shown in several works that some preprocessing techniques can improve data detection performance when they are applied to the channel matrix of MIMO wireless systems. In particular, these techniques can be used previously to K-Best tree search algorithms, and they are known to achieve successful results. Throughout this work, the performance and complexity of two preprocessing techniques (VBLAST ZF-DFE ordering and LLL lattice-reduction) are evaluated and compared. The LLL algorithm and a recently proposed fixed-complexity version of it are tested. In addition, a low-complexity implementation of the VBLAST ZF-DFE method is proposed. Results show that the LLL preprocessing is less costly than the VBLAST ZF-DFE ordering in average. Also, the BER curves of the K-Best detector in a 4 × 4 MIMO system reveal that the LLL method can only present better detection performance than the VBLAST ZF-DFE ordering for high SNRs and low values of K.