LAUSR

This paper investigates an intelligent reflecting surface (IRS) aided secure wireless powered communication network (WPCN), where a transmitter first harvests energy from a power station (PS), and then uses the collected energy to transmit information to multiple internet of things (IoT) devices in the form of multicast in the presence of multiple eavesdroppers. An IRS is deployed to enhance the efficiency of wireless energy transfer (WET) and secure wireless information transfer (WIT). Considering that the PS and transmitter belong to different service providers, we model this energy interaction through a Stackelberg game and propose an IRS-aided energy trading and secure communication (IRS-ETSC) scheme, in which the transmitter needs to pay an energy price as an incentive for the PS energy service. Specifically, the transmitter as the leader can control the energy price, WET time, two-stage phase shifts, and beamforming vector, while the PS as the follower can adjust the transmit power. To solve the non-convex leader game problem, we propose a two-step approach to decompose the original problem into two subproblems. The first subproblem can be solved independently by an efficient alternating optimization (AO) based algorithm, in which the closed-form optimal beamforming vector and energy phase shifts are alternately optimized. Then, the second subproblem is relaxed by semidefinite relaxation (SDR) and solved by an iterative algorithm based on block coordinate descent (BCD), where the optimal energy price, optimal WET time, and suboptimal information phase shifts can be obtained by golden section method and successive convex approximation (SCA) respectively. Both subproblems can converge to a stationary point. Numerical results show that compared with the traditional non-IRS scheme, the proposed IRS-ETSC scheme achieves utility improvement for both the PS and transmitter.