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InfoResearchPeer-reviewed
ABAE-RTN: A Deep Learning Framework for Robust Physical Layer Security in Radio Transformer Networks
- Published
- Record updated
Summary
Researchers propose ABAE-RTN, a deep learning framework for physical layer security in wireless networks. It combines adaptive beamforming, radio transformer networks and autoencoders, and injects controlled artificial noise to disrupt eavesdroppers. On the DeepMIMO dataset, across static (O1) and UAV-assisted dynamic (O1-Drone) environments, it reportedly improves secrecy rate, bit error rate and outage probability over LSTM and GNN baselines.