Joint Beamforming and Position Optimization for IRS-Aided SWIPT with Movable Antennas
Yanze Zhu, Qingqing Wu, Xinrong Guan, Ziyuan Zheng, Honghao Wang, Wen Chen, Yang Liu, and Yuan Guo

TL;DR
This paper introduces a joint optimization framework for IRS and movable antennas in SWIPT systems, enhancing information transfer and power harvesting in IoT networks through advanced beamforming and position strategies.
Contribution
It proposes a novel joint optimization approach for beamforming and antenna positioning in IRS-aided SWIPT, addressing non-convex challenges with an integrated algorithm.
Findings
Optimized IRS configurations outperform movable antennas in certain scenarios.
The proposed algorithm effectively balances information rate and power transfer.
Simulation confirms significant performance improvements with the joint optimization.
Abstract
Simultaneous wireless information and power transfer (SWIPT) has been envisioned as a promising technology to support ubiquitous connectivity and reliable sustainability in Internet-of-Things (IoT) networks, which, however, generally suffers from severe attenuation caused by long distance propagation, leading to inefficient wireless power transfer (WPT) for energy harvesting receivers (EHRs). This paper proposes to introduce emerging intelligent reflecting surface (IRS) and movable antenna (MA) technologies into SWIPT systems aiming at enhancing information transmission for information decoding receivers (IDRs) and improving receive power of EHRs. We consider to maximize the weighted sum-rate of IDRs via jointly optimizing the active and passive beamforming at the base station (BS) and IRS, respectively, as well as the positions of MAs, while guaranteeing the requirements of all EHRs.…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Energy Harvesting in Wireless Networks · Underwater Vehicles and Communication Systems
