Power Optimization of IRS-Assisted D2D System Based on Imperfect Channel

Abstract

Intelligent reflecting surface (IRS) is a promising technology that can help wireless communications achieve efficient spectrum and energy efficiency. However, because of its weak signal processing ability, it is difficult to get ideal channel state information (CSI). Under the imperfect channel state information hypothesis, we investigate a device-to-device (D2D) offload network. And an IRS is used to help calculate offloading from one set of task-intensive users to another set of idle users. We aim to jointly optimize transmit beamforming and IRS phase shifts to minimize system transmit power while requiring each user’s rate to meet the minimum rate constraint in the presence of channel errors. Unfortunately, the problem presented is nonconvex, and the imperfection of CSI makes it even more difficult to solve. Therefore, we apply the S-Procedure to convert the original problem to two effectively solvable semidefinite programming (SDP) subproblems and then solve them through the convex-concave procedure (CCP) algorithm and the alternate optimization method. Numerical results show the effectiveness of the algorithm and verify that the assistance of the IRS can greatly save the system transmit power.