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1.南京邮电大学通信与信息工程学院,江苏 南京 210003
2.南京邮电大学电子与光学工程学院,江苏 南京 210023
[ "李飞(1966- ),女,湖南长沙人,博士,南京邮电大学教授、博士生导师,主要研究方向为智能通信、智能信息处理、量子智能计算。" ]
[ "张杰(2001- ),男,江苏徐州人,南京邮电大学硕士生,主要研究方向为通感一体化与流体天线。" ]
[ "李汀(1979- ),男,江苏扬州人,博士,南京邮电大学副教授,主要研究方向为6G无线通信技术、量子计算、量子机器学习等。" ]
[ "宋云超(1988- ),男,江苏常州人,南 京邮电大学副教授、硕士生导师,主要研 究方向为5G/6G无线通信信号处理。" ]
收稿日期:2025-03-07,
修回日期:2025-05-20,
纸质出版日期:2025-06-25
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李飞,张杰,李汀等.流体天线辅助的ISAC系统通感动态加权联合波束成形设计[J].通信学报,2025,46(06):101-114.
LI Fei,ZHANG Jie,LI Ting,et al.Dynamic-weighted joint beamforming design for communication and sensing in fluid antenna-assisted ISAC system[J].Journal on Communications,2025,46(06):101-114.
李飞,张杰,李汀等.流体天线辅助的ISAC系统通感动态加权联合波束成形设计[J].通信学报,2025,46(06):101-114. DOI: 10.11959/j.issn.1000-436x.2025098.
LI Fei,ZHANG Jie,LI Ting,et al.Dynamic-weighted joint beamforming design for communication and sensing in fluid antenna-assisted ISAC system[J].Journal on Communications,2025,46(06):101-114. DOI: 10.11959/j.issn.1000-436x.2025098.
针对现有流体天线(FA)辅助通感一体化(ISAC)系统难以实现通信与感知动态权衡,且传统优化方法复杂度高的问题,提出一种基于加权联合优化通信与感知性能的FA辅助ISAC波束成形方案。首先,建立通信和速率与感知波束图增益加权和最大化模型,将通信速率最大化问题转换为加权最小均方误差(WMMSE)最小化形式,在发射功率约束下联合优化波束成形矩阵及收发端天线位置。然后,针对非凸的波束成形矩阵和FA位置优化问题,采用交替优化算法分解波束成形与位置优化子问题,结合泰勒展开与最大最小化(MM)算法构造凸松弛并推导闭式解。仿真结果表明,所提方案在通信与速率和波束图增益上明显优于传统ISAC系统,且通过调节权值可实现通信与感知性能的灵活权衡。
To address the challenges in achieving dynamic communication-sensing trade-offs and the high complexity of conventional optimization methods in existing fluid antenna (FA)-assisted integrated sensing and communication (ISAC) systems
a weighted joint optimization scheme for FA-assisted ISAC beamforming was proposed. Firstly
a weighted sum maximization model of communication sum-rate and sensing beam pattern gain was established. The communication rate maximization problem was transformed into a weighted minimum mean square error (WMMSE) minimization formulation
with joint optimization of the beamforming matrix and transceiver antenna positions under transmit power constraints. Then
for the non-convex optimization problem involving beamforming matrices and FA positions
an alternating optimization algorithm was employed to decompose it into beamforming and position optimization subproblems. Convex relaxations were constructed by integrating Taylor expansion and the majorization-minimization (MM) algorithm
and closed-form solutions were derived. The simulation results demonstrate that the proposed scheme significantly outperforms traditional ISAC systems in both total communication rate and beam pattern gain. Furthermore
flexible trade-offs between communication and sensing performance are achieved by adjusting weight parameters.
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