基于核独立分量分析的盲多用户检测算法

针对DS-CDMA通信系统中的盲多用户检测问题,提出了一种改进的核独立分量分析(KICA)算法.该算法首先将五阶收敛的牛顿迭代公式引入到传统的FastICA算法中,同时还引入了一种新的核函数——混合核函数来解决非线性混合信号的分离问题,从而实现了多用户信号检测.最后将所提出的算法与传统的FastICA算法和KICA算法进行仿真比较.结果表明:所提出的算法不仅收敛速度较快,而且具有较小的误码率.

Blind Multi-user Detection Algorithm Based on Kernel Independent Component Analysis

For the problem of blind multi-user detection in the DS-CDMA system,an improved kernel independent component analysis(KICA) algorithm was proposed.First,fifth-Newton iteration method was introduced to the traditional FastICA algorithm,and then,a new kernel function—hybrid kernel function was used to solve the separation of nonlinear mixed signals.Based on the proposed algorithm,the multi-user signal detection was realized.At last,the proposed algorithm was compared with the traditional FastICA and KICA algorithms,and the simulation results showed that the improved-KICA algorithm had the smaller bit error rate and good convergent speed.