A graph neural network method (CO-GNN) is proposed to jointly optimize beamforming, power allocation, and IRS phase shifts to maximize the sum secrecy rate of an IRS-assisted NOMA system facing external and internal eavesdroppers.
Robust beamforming design for an irs-aided noma communication system with csi uncertainty,
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Heterogeneous Secure Transmissions in IRS-Assisted NOMA Communications: CO-GNN Approach
A graph neural network method (CO-GNN) is proposed to jointly optimize beamforming, power allocation, and IRS phase shifts to maximize the sum secrecy rate of an IRS-assisted NOMA system facing external and internal eavesdroppers.