Optimal channel ranking using multiple channel permutation for QRM-MLD

Recently, high quality data transmission system has been widely researched. To achieve the better BER performance, several detection schemes in Multiple-Input Multiple-Output (MIMO) system have been studied. In the MIMO system, Maximum-Likelihood Detection (MLD) yields the optimal BER performance. However, it requires enormous computational complexity. Regarding the problem of actual implementation, Maximum-Likelihood (ML) Detection with QR Decomposition and M-algorithm (QRM-MLD) has been proposed for reducing the system complexity. On the other hand, this detection shows a little worse BER performance than MLD. Since QRM-MLD is used with a fewer symbol replica candidates than MLD, the error in the former detection stage causes an increase of the error in the latter stage. In this paper, we propose an optimal permutation of the channel matrix using QR Decomposition. The proposed scheme arranges channel matrix optimally, thereby absolute values of the diagonal components in upper triangular matrix are arranged ascending order. From the simulation results, the proposed scheme can improve the BER performance compared with the conventional method.