Transmit Power Minimization Algorithms for IRS-Assisted Cognitive Simultaneous Wireless Information and Power Transfer Networks

Intelligent reflecting surface (IRS) and cognitive simultaneous wireless information and power transfer (SWIPT) are regarded as potential key technologies to improve energy efficiency and spectrum utilization of wireless communication systems. This paper studied the IRS-aided cognitive SWIPT network based on a nonlinear energy harvesting model. In the network, a secondary transmitter simultaneously transmits information and energy to multiple secondary receivers, and each secondary receiver adopts the power splitting scheme to realize information decoding and energy harvesting. The aim is to minimize the transmit power of the secondary user transmitter by jointly optimizing the beamforming vector of the secondary transmitter, the power splitting coefficients of the secondary receivers, and the phase shifts of the IRS. In order to guarantee the information and energy transmission efficiency of the secondary users and limit the co-channel interference from the secondary users to the primary users, it is considered that the secondary receivers have the constraints of the minimum received signal-to-interference noise ratio, the minimum energy harvesting amount, and the values of power splitting coefficients, the secondary transmitter has the constraints of the maximum interference power values to the primary users, and the IRS has the constraints on its reflection phase shifts. The considered optimization problem is a non-convex quadratically constrained quadratic program problem with highly coupled optimization variables, which is difficult to solve. An alternating optimization algorithm based on the semidefinite relaxation and sequential rank one constraint relaxation techniques was proposed to solve the problem efficiently. In order to reduce the computation complexity, a low-complexity optimization algorithm based on IRS element grouping was further proposed. Simulation results show that compared to several benchmark algorithms, the proposed algorithms can effectively reduce the transmit power of the secondary transmitter.