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Compressive Learning in Communication Systems: A Neural Network Receiver for Detecting Compressed Signals in OFDM Systems

Compressive Learning in Communication Systems: A Neural Network Receiver for Detecting Compressed Signals in OFDM Systems

內容簡介

ABSTRACT Nowadays, the development of efcient communication system is necessary for future networks. Compressive sensing was proposed as a technique to save storage and energy by compressing signals using simple linear transformations. Although compressed signals can be perfectly recovered, the complexity of the reconstruction operation is high.


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