Liu, Z.; Wang, J.; Jiang, H.; Wang, J.; Li, X.; Xie, W. Physical Layer Security Performance Analysis of IRS-Aided Cognitive Radio Networks. Electronics2023, 12, 2615.
Liu, Z.; Wang, J.; Jiang, H.; Wang, J.; Li, X.; Xie, W. Physical Layer Security Performance Analysis of IRS-Aided Cognitive Radio Networks. Electronics 2023, 12, 2615.
Liu, Z.; Wang, J.; Jiang, H.; Wang, J.; Li, X.; Xie, W. Physical Layer Security Performance Analysis of IRS-Aided Cognitive Radio Networks. Electronics2023, 12, 2615.
Liu, Z.; Wang, J.; Jiang, H.; Wang, J.; Li, X.; Xie, W. Physical Layer Security Performance Analysis of IRS-Aided Cognitive Radio Networks. Electronics 2023, 12, 2615.
Abstract
Abstract- Cognitive radio (CR) play an important role in improving spectral efficiency (SE) of wireless communication, meanwhile, intelligent reflecting surface (IRS) is an effective technology to improve the secrecy performance of wireless communication system by adjusting the phase shift and amplitude of channel. Thus, we consider an IRS-aided multiple-input single-output (MISO) CR systems to enhance secrecy rate, which is consists of a single eavesdropping link, a primary network containing the primary receiver (PR), and secondary network including secondary receiver (SR) and the SR transmitter (SR-TX). Specifically, we minimize the transmit power of SR subject to secrecy capacity constraint and interference temperature (IT) constraint on PR, by jointly optimizing the beamforming vector and artificial noise (AN) constraints matrix at SR-TX as well as the phase shift matrix of IRS. Numerical results show that the different values of transmit antennas at the SR-TX and the number of IRS elements can significantly decrease the transmit power under the condition of ensuring secure communication.
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