摘要
A decoding method complemented by Maximum Likelihood (ML) detection for V-BLAST (Verti- cal Bell Labs Layered Space-Time) system is presented. The ranked layers are divided into several groups. ML decoding is performed jointly for the layers within the same group while the Decision Feedback Equalization (DFE) is performed for groups. Based on the assumption of QPSK modulation and the quasi-static flat fading channel, simulations are made to testify the performance of the proposed algorithm. The results show that the algorithm outperforms the original V-BLAST detection dramatically in Symbol Error Probability (SEP) per- formance. Specifically, Signal-to-Noise Ratio (SNR) improvement of 3.4dB is obtained for SEP of 10?2 (4×4 case), with a reasonable complexity maintained.
A decoding method complemented by Maximum Likelihood （ML） detection for V-BLAST （Vertical Bell Labs Layered Space-Time） system is presented. The ranked layers are divided into several groups. ML decoding is performed jointly for the layers within the same group while the Decision Feedback Equalization （DFE） is performed for groups. Based on the assumption of QPSK modulation and the quasi-static flat fading channel, simulations are made to testify the performance of the proposed algorithm. The results show that the algorithm outperforms the original V-BLAST detection dramatically in Symbol Error Probability （SEP） performance. Specifically, Signal-to-Noise Ratio （SNR） improvement of 3.4dB is obtained for SEP of 10^-2 （4×4 case）, with a reasonable complexity maintained.
基金
Supported by the National Natural Science Foundation of China (No.60172029).
