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Stationary points of a kurtosis maximization algorithm for blind signal separation and antenna beamforming

机译:盲信号分离和天线波束成形的峰度最大化算法的平稳点

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摘要

Blind source separation has been the subject of extensive research. In particular, blind antenna beamforming is an effective signal separation technique for communication systems to combat co-channel interference. Among many potential candidate approaches, the simple constant modulus algorithm (CMA) has been widely studied and used in practice. The CMA is designed to capture and separate signals with negative kurtosis. However, when some signals have positive kurtoses, the CMA is unable to capture and separate these sources. We show that the kurtosis maximum algorithm (KMA) can capture signals with both the positive and negative kurtoses. Its global convergence proof is presented for noiseless systems with multiple signals sources and for systems with a single source and zero-kurtosis (such as Gaussian) additive noise.
机译:盲源分离一直是广泛研究的主题。尤其是,盲天线波束成形是一种有效的信号分离技术,可用于通信系统以对抗同信道干扰。在许多潜在的候选方法中,简单恒模算法(CMA)已被广泛研究并在实践中使用。 CMA旨在捕获和分离峰度为负的信号。但是,当某些信号具有阳性的Kurtoses时,CMA无法捕获和分离这些信号源。我们显示峰度最大算法(KMA)可以捕获具有正和负Kurtoses的信号。针对具有多个信号源的无噪声系统以及具有单个源和零峰度(例如高斯)加性噪声的系统,提供了其全局收敛性证明。

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