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Multi-user Detection of DS-CDMA Based on Improved-FastICA

机译:基于FastICA的DS-CDMA多用户检测

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Multi-user detection (MUD) is used to control multiple access interference (MAI) and promote system performance and capacity, which is one of the key technology for CDMA system. Independent component analysis (ICA) aims to recover a set of unknown mutually independent source signals from theirs observed mixtures without knowledge of the mixing coefficients. FastICA, one of the ICA methods, has been successfully applied in various fields. But the classical FastICA does not converge quickly. In multi-user detection of direct sequence code division multiple access (DS-CDMA) system, we proposes an Improved-FastICA algorithm to reduce multiple access interference (MAI). The improved-FastICA algorithm uses a new Fifth-order Newton iterative method to estimate the negentropy. The experimental results show that the improved algorithm has the advantages of smaller bit error rate than traditional algorithm. The Improved-FastICA is more suitable for applications in DS-CDMA system.
机译:多用户检测(MUD)用于控制多址干扰(MAI)并提高系统性能和容量,这是CDMA系统的关键技术之一。独立成分分析(ICA)的目的是在不了解混合系数的情况下,从其观察到的混合物中恢复出一组未知的相互独立的源信号。 FastICA是ICA的一种方法,已成功应用于各个领域。但是经典的FastICA并没有很快收敛。在直接序列码分多址(DS-CDMA)系统的多用户检测中,我们提出了一种改进的FastICA算法来减少多址干扰(MAI)。改进的FastICA算法使用一种新的五阶牛顿迭代法来估计负熵。实验结果表明,与传统算法相比,改进算法的误码率较小。改进型FastICA更适合于DS-CDMA系统中的应用。

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