A Spectral Efficiency Design for Active IRS-assisted SWIPT System via Semidefinite Relaxation Method

Active intelligent reflecting surfaces (IRS) with phase-shift and amplifier capabilities have arisen as a solution relied upon to improve spectral/energy efficiency of wireless systems, as they outperform conventional passive techniques/without IRS assistance. In this work, the simultaneous wireless information and power transfer (SWIPT) downlink is supported by an active IRS, where a multi-antenna base station (BS) broadcasts both information and power to multiple hybrid power-splitting (PS) users. The target of sum data rate maximization is to study the constraints of user energy harvesting thresholds and power transmission limitations of BS and active IRS. To tackle this complicated issue, iterative algorithms are proposed to find the optimal beamforming vector, PS coefficients, and IRS parameters, as amplification factors and phase shift. A joint optimization framework using alternating optimization, semidefinite relaxation, and non-convex approximations is used. Finally, simulation experiments are performed to assess that the proposed iterative algorithms of the active IRS scheme converge fast and achieve better sum rate results than conventional baseline schemes.