基于WINC的自适应主分量提取的盲多用户检测算法

The usage of adaptive principal components extraction based on WINC in blind multiuser detection

本文提出了一种新的基于子空间追踪的盲多用户检测算法。首先分析了基于加权信息准则(WINC)的自适应主分量提取(APEX)方法,然后将AIC准则与之结合使其能用于主分量个数未知的情况,最后还增加了一次正交化操作以加快收敛速度。仿真结果显示,本文提出的算法在用户数目较多的情况下比经典的OPAST算法有着更好的性能。

In this paper,a novel blind muhiuser detection algorithm based on subspace tracking is proposed. First,we analyze a Adaptive Principal Components Extraction（APEX） algorithm based on Weighted Information Criterion（ WINC ）, and then the AIC crite- rion is added to the algorithm in order to fit the case that the number of users is unknown. Finally, we use an orthogonal operation to fast the convergence speed. We then compare it with the OPAST algorithm, the result shows that when the number of users is big, the pro- posed algorithm performs much better than OPAST.