Active Intelligent Reflecting Surface Assisted Secure Computation of Wireless Powered MEC

Intelligent reflecting surfaces (IRS) have been extensively employed to enhance physical layer security. However, passive IRS face limitations in enhancing secrecy performance due to the multiplicative attenuation effect. To address this limitation, we propose an innovative design leveraging active IRS to enhance the secure computing performance of the mobile edge computing (MEC) system in the presence of eavesdropper. Furthermore, wireless power transfer (WPT) technology is integrated to furnish a continuous energy supply to edge devices, thereby facilitating the execution of computational tasks. In the proposed framework, energy signals are initially transmitted by the base station (BS) to charge multiple users. The harvested energy is subsequently used by the users for local computation and partial task offloading in the presence of eavesdropper. Simultaneously, active IRS is deployed to enhance energy harvesting efficiency and secure task offloading. To maximize the secure computation rate, we jointly optimize the time allocation for WPT and task offloading, the energy and receive beamforming of the BS, the reflection coefficients of the active IRS, the user’s local computation frequency, and the transmit power. The resulting non-convex optimization problem is addressed through an iterative algorithm based on block coordinate descent (BCD). Simulation results indicate that the proposed active IRS-based scheme achieves substantial improvements in secure computation rate compared to existing benchmark methods.