Identify Modulation for Communications and Radar Using Deep Learning (.PDF Download)
July 25, 2019
Modulation identification is an important function for an intelligent receiver. It has numerous applications in cognitive radar, software-defined radio, and efficient spectrum management. To identify both communications and radar waveforms, it’s necessary to classify them by modulation type. For this, meaningful features can be input to a classifier.
While effective, this procedure can require extensive effort and domain knowledge to yield an accurate classification. This article will explore a framework to automatically extract time-frequency features from signals. The features can be used to perform modulation classification with a deep-learning network. Alternate techniques to feed signals to a deep-learning network will be reviewed.
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