Radio fingerprinting using convolutional neural networks
In this thesis, we describe a method for uniquely identifying a specific radio among nominally similar devices using a combination of software defined radio (SDR) sensing capability and machine learning (ML) techniques. Our approach of radio fingerprinting applies ML over raw I/Q samples without s...
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Online Access: | http://hdl.handle.net/2047/D20316368 |
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