一种低复杂度的近似最大似然MIMO检测算法

Complexity reduction ML detection algorithm for MIMO system

为保证无线传感器网络协作式V-BLAST传输中,在较高的检测性能的前提下大大降低算法复杂度,提出一种低复杂度的近似最大似然检测算法.将传统的V-BLAST算法性能最好一层解的邻域作为候选判决集合,并以此邻域内每一个符号作为初始值进一步采用传统的V-BLAST算法反馈判决其他层的符号,采用最大似然准则对候选向量进行判断.该方法有效减小了最大似然检测算法检测向量的数目,降低了算法的复杂度.仿真结果表明该算法具有良好的综合性能.

Aiming at reducing the computational complexity greatly and achieving high detection performance in cooperative MIMO-based WSN,a new complexity reduction ML detection algorithm is proposed.Using conventional V-BLAST algorithm,the best performance layer is found,and the neighborhood is considered to be candidate set.Regard the every symbol in the candidate set as initial value,we adopt V-BLAST algorithm again to detect the symbol of other layers.At last,we use the maximum likelihood criterion to judge the candidate vector.Because the number of constellation point in the maximum likelihood detection algorithm is reduced effectively,the complexity of the algorithm decrease greatly.The simulation results show that the proposed scheme obtains good comprehensive performance.