长码MIMO CDMA信道的一阶聚类盲估计
doi: 10.3724/SP.J.1146.2005.00712
A First-Order Statistical Clustering Method for Long-Code MIMO CDMA Blind Channel Estimation
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摘要: 该文提出了一种长码多输入多输出CDMA系统的信道盲估计方法。使用解相关匹配滤波器作为接收机前端，其输出信号可以剖分为信道矢量张成的线性空间。使用聚类算法提取集合的中心，从而仅利用解相关器输出的一阶统计量便可很好地估计出信道参数。同时对K-均值聚类算法的初始值设定进行了改进以提高收敛速度。所提出的算法有较低的计算复杂度。仿真结果表明该算法的有效性以及对信道阶数过估计有很好的鲁棒性。Abstract: A blind channel estimation method is presented for the Multiple-Input-Multiple-Output (MIMO) CDMA system employing long spreading codes. To estimate channel parameters, a decorrelating matched filter is applied as front-end at the receiver. The matched filter outputs consist of the signal space spanned by the users channel vector and the centers of the sets are extracted by clustering procedure. Then the channel parameters are estimated via the first-order statistics of the filter outputs. The K-mean clustering algorithm is improved in class centers initialization for fast convergence. The proposed method has low computational complexity. Simulation results illustrate the effectiveness of the proposed method and the robustness to channel order overestimation.
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