Exploiting adaptive particle swarm optimization and penalty function methods for secrecy rate maximization in secure IRS-aided SWIPT system
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Abstract
In this work, the physical layer security of an intelligent reflecting surface (IRS)-assisted simultaneous wireless information and power transfer (SWIPT) system is investigated in the presence of an eavesdropper (Eve). The goal is to maximize the secrecy rate while satisfying the harvested energy threshold at the power-splitting (PS) receiver. By optimizing the phase shifts at the IRS, the signal is enhanced at the receiver while reduced at Eve. The solution approach via the penalty function technique and adaptive particle swarm optimization (PSO) is proposed and performed through numerical experiments. Eventually, the impacts of system factors such as transmission power and energy harvesting threshold on the convergent behavior and the secrecy rate are presented, and the future direction is discussed.
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References
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