A fast QR decomposition algorithm with optimal detection order is proposed in this paper for common used MIMO nonlinear detection, including sorted QR decomposition (SQRD) , sphere decoding (SD), K-best/QR decomposition and M algorithm ( QRM) and so on. Using this algorithm, the receiver does QR decomposition of the channel matrix firstly, determines the best order of detection from the upper triangular matrix; R, and arranges the columns of R according to the optimal detection order; then, the receiver does QR decomposition of the rearrangement matrix of R for a second time, which is the QR decomposition results with the optimal detection order. Compared with the existing QR decomposition algorithm, getting its detection order according to the diagonal elements' modulus of R, the proposed fast QR decomposition algorithm can improve detection performance because of its optimal detection order. Simulation results show when bit error rate ( BER) equals 10-3 with the antenna configuration being 4x4 and 6x6, the proposed algorithm can save signal to noise ratio (SNR) in 1 dB and 2 dB, respectively. Compared with the existing QR decomposition algorithm, getting its detection order according to signal to interference and noise ratio (SINR) , the proposed algorithm can reduce 25% times of complex multiplications and 33% times of complex additions with the same BER performance.%针对多输入多输出系统中常用的非线性检测算法,如排序QR分解(Sorted QR Decomposition,SQRD)、球型译码(Sphere Decoding,SD)、K-Best或QRM( QR Decomposition and M algorithm)等,提出了一种具有最优检测顺序的QR快速分解方法,作为检测前的预处理操作.该算法首先对信道矩阵进行第一次QR分解,根据所得上三角矩阵R可确定最优的检测顺序,并按该顺序对R进行列重排.然后对R进行第二次QR分解,即得具有最优检测顺序的QR分解结果.与现有的基于R对角元素的模值排序的QR分解算法相比,本算法可保证检测顺序最优从而性能最优.仿真结果表明天线配置为4×4和6×6时,在误码率10-3处可节约信噪比分别为:1dB和2dB;与现有的基于信干噪比排序的QR分解算法相比,本算法与其性能一致的基础上可节约25％的复乘法次数和33％的复加法次数.
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