Improvement of QRM-MLD Method in MIMO Systems Considering Noise Power Estimation

In this paper, we propose a new method for improving the bit error rate (BER) and the computational complexity in Maximum Likelihood Detection employing QR decomposition and the M-algorithm (QRM-MLD) which provides high performance among the signal separation techniques for Multiple Input Multiple Output (MIMO). QRM-MLD utilizing noise power estimation is regarded as an effective method to reduce the computational complexity. However, the method can not cope with the gap from the average noise power at each stage. In the proposed method, we can obtain better performance by setting thresholds according to the variations in the noise power at each stage. Simulation results show that the proposed method can improve the BER and the computational complexity compared with the conventional method.