一种高性能低复杂度的V-BLAST检测方案

基于排序正交上三角分解(QR)提出了一种新的列表V-BLAST检测方案，对第1层采用列表检测产生多个候选符号，当候选符号数等于星座大小时，提出了一种修正的排序QR分解算法，后续各层作连续干扰抵消检测，在得到的多组候选符号中做最小欧氏距离(MED)搜索，输出最佳组作为检测结果．分析和仿真表明，与现有算法相比该方案能以较低的复杂度获得很好的性能，当天线数目比较少(5以下)时性能接近于ML检测．为了进一步降低运算复杂度，提出了在MED搜索过程中设置门限的处理方式，并给出了一种门限值的选取方法．结果表明，该方法可以在保证性能损失很小的情况下使运算量减少一半以上．

Low-complexity V-BLAST detection scheme with high performance

Based on sorted QR decomposition, a new list V-BLAST detection scheme is proposed. List detection is adopted for the first layer to produce several candidate symbols. A modified sorted QR decomposition is also proposed for the case of the number of candidates equal to the constellation size. Several groups of candidate symbols can be obtained when successive interference cancellation is applied to the following layers, and the minimum Euclidean distance (MED) search is used to choose one as the output. Analysis and simulation show that the proposed scheme can achieve very good performance with low complexity. When the number of antennas is less than 5, it can achieve near ML detection performance. A threshold can be set in the process of searching MED to further reduce the complexity, and the method for determining the threshold value is also given. Simulation results show that the method can reduce more than one half of the complexity while suffering a little performance loss.