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<p>In order to avoid eavesdropping with no additional hardware, a secure non-orthogonal multiple access based quadrature spatial modulation (NOMA-QSM) scheme is proposed. Artificial noise (AN) is added to the information-carrying signal at the transmitter, causing interference at the eavesdropper while not affecting the legitimate users. A deep learning (DL) based channel estimation is also proposed with the rectified linear unit. Simulation results show that due to the addition of AN, the sum secrecy rate of the system increases to 1.6 bits/s/Hz at a 40 dB signal-to-noise ratio (SNR). The sum secrecy rate of the system increases as the number of transmitting antennas (TAs) increases. The proposed DL-based channel estimation scheme provides comparable performance as that of the minimum mean square estimator at low and high SNR values. At 20 dB SNR, the mean square estimation error for the proposed scheme is approximately -17 dB when two TAs are used. This study also analyzes the effect of imperfect channel state information and imperfect successive interference cancellation on the secrecy rate of users.</p>

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Deep Learning Based Channel Estimation and Artificial Noise Aided Security for NOMA-QSM System

  • 期刊论文

  • 发表日期：

    2025年3月1日

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  • Shekhar Pratap Singh,
  • Pyari Mohan Pradhan

摘要

In order to avoid eavesdropping with no additional hardware, a secure non-orthogonal multiple access based quadrature spatial modulation (NOMA-QSM) scheme is proposed. Artificial noise (AN) is added to the information-carrying signal at the transmitter, causing interference at the eavesdropper while not affecting the legitimate users. A deep learning (DL) based channel estimation is also proposed with the rectified linear unit. Simulation results show that due to the addition of AN, the sum secrecy rate of the system increases to 1.6 bits/s/Hz at a 40 dB signal-to-noise ratio (SNR). The sum secrecy rate of the system increases as the number of transmitting antennas (TAs) increases. The proposed DL-based channel estimation scheme provides comparable performance as that of the minimum mean square estimator at low and high SNR values. At 20 dB SNR, the mean square estimation error for the proposed scheme is approximately -17 dB when two TAs are used. This study also analyzes the effect of imperfect channel state information and imperfect successive interference cancellation on the secrecy rate of users.