Abstract
Combining simultaneous wireless information and power transfer (SWIPT) and intelligent reflecting surface (IRS) is a feasible scheme to enhance the energy efficiency (EE) performance. In this paper, we investigate a multiuser IRS-aided multiple-input single-output (MISO) system with SWIPT. For the purpose of maximizing the EE of the system, we jointly optimize the base station (BS) transmit beamforming vectors, the IRS reflective beamforming vector and the power splitting (PS) ratios, while considering the maximum transmit power budget, the IRS reflection constraints and the quality of service (QoS) requirements containing the minimum data rate and the minimum harvested energy per user. As the proposed EE maximization problem is non-convex and extremely complex, we propose an efficient alternating optimization (AO) algorithm by decoupling the original problem into three subproblems which are tackled iteratively by using the Dinkelbach method. In particular, we apply the successive convex approximation (SCA) as well as the semi-definite relaxation (SDR) techniques to solve the non-convex transmit beamforming and reflective beamforming optimization subproblems. Numerical results confirm the effectiveness of the AO algorithm as well as the benefit of deploying IRS for enhancing the EE performance compared with the benchmark schemes.
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