Beamforming Optimization for Active Intelligent Reflecting Surface-Aided SWIPT
Ying Gao, Qingqing Wu, Guangchi Zhang, Wen Chen, Derrick Wing Kwan Ng,, Marco Di Renzo

TL;DR
This paper proposes optimized beamforming strategies for an active IRS-assisted SWIPT system, demonstrating significant improvements in energy transfer range, harvested energy, and data rates over benchmarks, especially with active IRS deployment near users.
Contribution
It introduces novel joint transmit and reflect beamforming optimization algorithms for active IRS-aided SWIPT, proving SDR tightness and developing efficient suboptimal solutions.
Findings
Active IRS significantly enhances WPT and SWIPT performance.
Proposed algorithms outperform benchmark schemes in simulations.
Active IRS deployment near users is highly effective.
Abstract
In this paper, we study an active IRS-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, an active IRS is deployed to assist a multi-antenna access point (AP) to convey information and energy simultaneously to multiple single-antenna information users (IUs) and energy users (EUs). Two joint transmit and reflect beamforming optimization problems are investigated with different practical objectives. The first problem maximizes the weighted sum-power harvested by the EUs subject to individual signal-to-interference-plus-noise ratio (SINR) constraints at the IUs, while the second problem maximizes the weighted sum-rate of the IUs subject to individual energy harvesting (EH) constraints at the EUs. The optimization problems are non-convex and difficult to solve optimally. To tackle these two problems, we first rigorously prove that dedicated energy beams…
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