Digitally Modulated Signal Classification based on Higher Order Statistics of Cyclostationary Process
نویسندگان
چکیده
منابع مشابه
Compressive Higher Order Cyclostationary Statistics
The application of nonlinear transformations to a linearly modulated communication signal for the purpose of revealing hidden periodicities has proven to be useful for automatic modulation recognition (AMR). The fact that the hidden periodicities, referred to as Higher Order Cyclostationary Statistics (HOCS), are compressible in the Fourier domain motivates the use of compressive sensing (CS) a...
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The application of nonlinear transformations to a cyclostationary signal for the purpose of revealing hidden periodicities has proven to be useful for applications requiring signal selectivity and noise tolerance. The fact that the hidden periodicities, referred to as cyclic moments, are often compressible in the Fourier domain motivates the use of compressive sensing (CS) as an efficient acqui...
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The framework of computing Higher Order Cyclostationary Statistics (HOCS) from an incoming signal has proven useful in a variety of applications over the past half century, from Automatic Modulation Recognition (AMR) to Time Difference of Arrival (TDOA) estimation. Much more recently, a theory known as Compressive Sensing (CS) has emerged that enables the efficient acquisition of high-bandwidth...
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ژورنال
عنوان ژورنال: Journal of Broadcast Engineering
سال: 2014
ISSN: 1226-7953
DOI: 10.5909/jbe.2014.19.2.195