A Novel Neural Network Blind Multi-user Detection Algorithm

Shen Fang, Sun Yunshan, Z. Liyi
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引用次数: 2

Abstract

Blind multi-user detection (BMUD) is a key technology in CDMA to improve communication quality. This paper introduced FNN (feed-forward neural network) to BMUD algorithm. It combined FNN with CMA algorithm, constructed a cost function, optimized FNN weights and parameters by LMS and then realized BMUD. Compared with traditional CMA blind multi-user algorithm, simulation results indicate new algorithm improves the performances in bit-error ratio, following ability and soon.
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一种新的神经网络盲多用户检测算法
盲多用户检测是CDMA中提高通信质量的关键技术。将FNN(前馈神经网络)引入到BMUD算法中。将FNN与CMA算法相结合,构造代价函数,利用LMS优化FNN的权值和参数,实现BMUD。仿真结果表明,与传统的CMA盲多用户算法相比,新算法在误码率、跟踪能力和快速性等方面都有所提高。
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