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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.11148 |
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| _version_ | 1866917080152932352 |
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| author | Zhu, Yanze Wu, Qingqing Guan, Xinrong Zheng, Ziyuan Wang, Honghao Chen, Wen Liu, Yang Guo, Yuan |
| author_facet | Zhu, Yanze Wu, Qingqing Guan, Xinrong Zheng, Ziyuan Wang, Honghao Chen, Wen Liu, Yang Guo, Yuan |
| contents | 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. To tackle this challenging task due to the non-convexity of associated optimization, we develop an efficient algorithm combining weighted minimal mean square error (WMMSE), block coordinate descent (BCD), majorization-minimization (MM), and penalty duality decomposition (PDD) frameworks. Besides, we present a feasibility characterization method to examine the achievability of EHRs' requirements. Simulation results demonstrate the significant benefits of our proposed solutions. Particularly, the optimized IRS configuration may exhibit higher performance gain than MA counterpart under our considered scenario. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_11148 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Joint Beamforming and Position Optimization for IRS-Aided SWIPT with Movable Antennas Zhu, Yanze Wu, Qingqing Guan, Xinrong Zheng, Ziyuan Wang, Honghao Chen, Wen Liu, Yang Guo, Yuan Information Theory 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. To tackle this challenging task due to the non-convexity of associated optimization, we develop an efficient algorithm combining weighted minimal mean square error (WMMSE), block coordinate descent (BCD), majorization-minimization (MM), and penalty duality decomposition (PDD) frameworks. Besides, we present a feasibility characterization method to examine the achievability of EHRs' requirements. Simulation results demonstrate the significant benefits of our proposed solutions. Particularly, the optimized IRS configuration may exhibit higher performance gain than MA counterpart under our considered scenario. |
| title | Joint Beamforming and Position Optimization for IRS-Aided SWIPT with Movable Antennas |
| topic | Information Theory |
| url | https://arxiv.org/abs/2511.11148 |