Joint Energy Beamforming and Optimization for Intelligent Reflecting Surface Enhanced Communications

To face the scarcity of wireless spectrum resources and explosive energy consumption due to rapid growth of mobile devices and Internet of Things terminals, intelligent reflecting surface (IRS) has recently gained a lot of attention and become as one of the promising solutions. In this paper, we consider an IRS-enhanced multiple-input single- output (MISO) system, in which the IRS is wireless powered by the access point (AP) in power splitting scheme. We aim to maximize the signal-to-noise ratio (SNR) of the end user by jointly optimizing the AP's beamforming as well as the phase-shift and the power splitting ratio of the IRS elements. To tackle the non-convexity of the formulated problem due to the coupling of optimization variables, we devise a two-stage approximation algorithm by analyzing and then decomposing the structure of the problem. Specifically, the algorithm first tunes the phase-shift of IRS elements to align the equivalent channel of IRS reflected path to that of the direct link. After that, we adopt a successive convex approximation based method to achieve a near optimal solution for the reformulated problem iteratively. The simulation results show that our proposed two-stage approximation algorithm can solve the jointly SNR maximization problem efficiently.