华南理工大学电子与信息学院, 广东 广州 510006
唐杰(1986年生),男;研究方向:通信感知一体化;E-mail:eejtang@scut.edu.cn
收稿:2025-02-04,
录用:2025-03-14,
网络出版:2025-05-21,
纸质出版:2025-07-25
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唐杰,范峻媛,张延波等.面向动态物联的通信、感知与传能一体化方法[J].中山大学学报(自然科学版)(中英文),2025,64(04):22-30.
TANG Jie,FAN Junyuan,ZHANG Yanbo,et al.Integrated communication, sensing and energy transfer for dynamic internet of things[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2025,64(04):22-30.
唐杰,范峻媛,张延波等.面向动态物联的通信、感知与传能一体化方法[J].中山大学学报(自然科学版)(中英文),2025,64(04):22-30. DOI: 10.13471/j.cnki.acta.snus.ZR20250020.
TANG Jie,FAN Junyuan,ZHANG Yanbo,et al.Integrated communication, sensing and energy transfer for dynamic internet of things[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2025,64(04):22-30. DOI: 10.13471/j.cnki.acta.snus.ZR20250020.
将无线能量传输引入通感一体化框架,提出了一种综合通信需求、移动能量设备追踪与能量补给的通信感知传能一体化系统设计方案,基站可同时执行通信数据传输、无线能量传输和感知追踪三重功能。其中,基站利用下行信号同时实现无线能量传输和高效数据通信,并利用回波信号实现对移动能量设备的定位。首先,提出了一种迭代式目标追踪算法,将实时后验追踪误差作为感知性能的衡量指标,以通信信噪比、感知误差等约束条件下的实时能量补给效率最大化问题为目的建立模型。该通信与感知传能联合波束形成问题为非凸优化问题,利用半正定松弛、辅助变量等方法将问题转换为凸问题求解。仿真结果表明:所提出的算法通过优化通信与传能波束有效提高了系统的能量收集效率,且感知信息同时被用于优化传能和通信链路,以实现通信、感知、能量补给的一体化融合。
This paper proposes a system design for integrated sensing, communication, and power transfer(ISCPT) which jointly addresses communication requirements, mobile energy device (MED) tracking, and energy replenishment. The proposed system enables a base station to simultaneously perform three functions: data communication, wireless power transfer, and sensing-based tracking. Specifically, the base station leverages downlink signals for simultaneous wireless power transfer, and efficient data communication, while employing their echoes to localize the MED. An iterative target tracking algorithm is developed, where the real-time posterior tracking error serves as a metric for sensing accuracy. An optimization problem is formulated to maximize real-time energy replenishment efficiency, subject to constraints on communication signal-to-noise ratio(SNR) and sensing error. The joint beamforming problem for communication, sensing, and power transfer, initially formulated as a non-convex optimization problem, is transformed into a convex one via semidefinite relaxation and the introduction of auxiliary variables. Simulation results demonstrate that the proposed algorithm significantly improves the system’s energy harvesting efficiency by jointly optimizing communication and power transfer beamforming. Furthermore, the sensing information is effectively leveraged to optimize both power transfer and communication links, thereby achieving the integrated fusion of communication, sensing, and energy replenishment.
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