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• W2146514432 abstract "In this paper, we propose an algorithm for the classification of digital amplitude-phase modulated signals in flat fading channels with non-Gaussian noise. The additive noise is modeled by a Gaussian mixture distribution, a well-known model of man-made and natural noise that appears in most radio channels. The classifier utilizes a variant of the expectation-maximization algorithm to estimate the channel and noise parameters without the aid of training symbols. With these estimates, the signal is classified using a hybrid likelihood ratio test. Results are presented which show that the proposed classifier's performance approaches that of the ideal classifier with perfect knowledge of the channel state and noise distribution." @default.
• W2146514432 created "2016-06-24" @default.
• W2146514432 creator A5065349422 @default.
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• W2146514432 date "2011-08-01" @default.
• W2146514432 modified "2023-10-13" @default.
• W2146514432 title "Maximum-Likelihood Classification of Digital Amplitude-Phase Modulated Signals in Flat Fading Non-Gaussian Channels" @default.
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• W2146514432 doi "https://doi.org/10.1109/tcomm.2011.051711.100184" @default.
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