一种结合ML检测的高性能V-BLAST系统

Higher performance V-BLAST system complemented by ML detection

提出了一种改进的V BLAST(VerticalBellLabsLayeredSpace Time)检测算法,接收信号向量经过信道矩阵排序与QR分解的前馈滤波后,对分层分组.每个分组内部并行进行最大似然检测,分组间使用判决反馈式干扰抵消.以QPSK调制方式为例,仿真验证了该算法在准静态平坦衰落信道中的误比特(BER)性能,与V BLAST算法、ML DFE(MaximumLikelihood DecisionFeedbackEqualization)算法比较结果表明有较低的复杂度,能有效地提高系统性能,在10-2的BER可获得1.6～2.8dB增益.

A modified detection algorithm for the V-BLAST (Vertical Bell Labs Layered Space-Time) system is presented. The reveived signal vector is feedforward filtered by QR factorization of the sorted channel matrix. The ranked layers are divided into serveral groups. The layers within the same group are detected using the maximum likelihood (ML) algorithm while the decision feedback interference cancellation are performed between 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. Results show that the algorithm outperforms the original V-BLAST and ML-DFE(Maximum Likelihood-Decision Feedback Equalization) algorithm dramatically in bit error ratio (BER) performance. Specifically, signal-to-noise ratio (SNR) improvement of 1.6-2.8 dB is obtained for BER of 10-2, while maintaining a reasonable complexity.