# Quantum PSO-Based Optimization of Secured IRS-Assisted Wireless-Powered IoT Networks
### Related Work
#### 1.1.3 IRS-Assisted Secure Communication  
Recent studies show significant interest in secure IRS-assisted communications systems that integrate intelligent reflecting surfaces with physical layer security (PLS) techniques [8; 27; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42], as summarized in Table 2. In particular, [PERSON] et al. [32] investigated how incorporating artificial noise into transmit beamforming enhances the secrecy rate in IRS-assisted communications systems, particularly in scenarios where the number of eavesdroppers exceeds transmit antennas. In [33], [PERSON] et al. employed an alternating optimization algorithm to address the problem of maximizing the secrecy rate. They derived the transmit covariance in closedform and obtained the phase shift solutions using a semi-closed form. [PERSON] et al. investigated PLS in cooperative NOMA systems by considering both amplify-and-forward (AF) and decode-and-forward (DF) protocols [34]. They derived analytical expressions for the strictly positive secrecy capacity and secrecy outage probability (SOP). [PERSON] and [PERSON] [35] explored cognitive two-way relay networks, focusing on cooperative secure transmissions through beamforming design. In this setup, a cognitive transmitter with multiple antennas facilitates the transmission of signals from two primary transmitters while safeguarding them against wiretapping by a single-antenna eavesdropper. Similarly, [PERSON] et al. [36] studied the secrecy performance of a reconfigurable intelligent surface (RIS)-assisted wireless communication system in the presence of an eavesdropper, assuming that the RIS was positioned between the source and the legitimate user to improve link security. A simultaneously transmitting and reflecting IRS was employed in [37] to enhance the performance of PLS in MISO systems. Concurrently transmitting and reflecting the signals achieved MISO system security enhancement and communications effectiveness. Three different transmission modes (energy splitting, temporal splitting, and mode selection) were examined by the authors. Their method simultaneously optimizes the transmission and reflection coefficients as well as the IRS beamforming vectors. To enhance secrecy rates, AN was considered by [PERSON] et al. [8] to study PLS. The covariance matrix for AN, the IRS phase shift parameters, and the transmit precoding matrix at the base station are jointly optimized by the proposed scheme. To improve the secrecy rate, the block coordinate descent (BCD) technique is employed. [PERSON] et al. examined the cumulative distribution function and probability density function of the signal-to-noise ratio in the presence of an IRS [38]. By considering stochastic geometry approaches, they derived the SOP and secrecy rate by utilizing those distribution functions. The authors in [39] proposed an IRS-assisted PLS scheme for 5G-enabled Industrial Internet of Things (IIoT) networks, aimed at enhancing the weighted secrecy sum rate (WSSR) in industrial wireless environments with eavesdroppers. Their approach involves jointly optimizing active and passive beamforming vectors to improve user secrecy rates. To maximize WSSR, they employ a stable matching algorithm to optimally assign IRSs for secure data exchange between industrial units. Recently, several studies have explored the potential of integrating an IRS into WPINs for PLS. [PERSON] et al., in [40], proposed a study for PLS in an IRS-aided WPC system with a passive eavesdropper, proposing three deployment modes for the IRS. Optimal phase shifts are designed to enhance energy and information reception, and closed-form expressions for ergodic secrecy capacity are derived. Their results show significant performance gains for Modes I and II, while Mode III excels under low power or fewer IRS elements. [PERSON] et al., in [41], examined how security can be enhanced by combining an IRS with an EH jammer for uplink transmissions, effectively countering malicious eavesdroppers.