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arXiv 2603.16632eess.SPcs.ITcs.NImath.ITmath.OC
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面向不完美信息的ISAC系统无线电资源管理最优配置:从资源经济视角出发

Optimal Radio Resource Management for ISAC Under Imperfect Information: A Resource Economy-Driven Perspective

Ruhr University Bochum(波鸿鲁尔大学)

Luis F. Abanto-Leon, Setareh Maghsudi

AI总结:

本文研究了下行一体化感知与通信系统中无线电资源管理的设计,通过联合优化时隙分配、波束适应、功能选择和用户-目标配对,以在不完美信息下实现资源消耗最小化。

摘要:

本文研究了下行一体化感知与通信系统中无线电资源管理的设计,联合优化时隙分配、波束适应、功能选择和用户-目标配对,以在不完美信息下实现资源消耗最小化。时隙分配将离散的信道使用次数分配给目标和用户,波束适应选择具有合适方向、功率级别和波束宽度的发射和接收波束。功能选择确定每个时隙用于感知、通信或同时操作,用户-目标配对指定在同一时隙内共同服务的用户和目标。为确保可靠运行,考虑了由运动、量化、反馈延迟和硬件限制引起的不完美信息。通过多目标函数最小化能量和时间消耗来实现资源节约,严格优先考虑时间节约。所得到的RRM问题被表述为一个半无限、非凸的混合整数非线性规划(MINLP)问题。鉴于缺乏通用解决此类问题的方法,我们提出了一种定制方法,利用问题的底层结构来揭示隐藏的凸性。这使问题能够精确地重新表述为混合整数半定规划(MISDP),可以全局最优求解。仿真揭示了所考虑的RRM组件之间的关键依赖关系,并显示所提出的方法在基准方案上实现了显著的性能改进,最大收益达88%。

英文摘要:

This work investigates the radio resource management (RRM) design for downlink integrated sensing and communications (ISAC) systems, jointly optimizing timeslot allocation, beam adaptation, functionality selection, and user-target pairing, with the goal of economizing resource consumption under imperfect information. Timeslot allocation assigns a number of discrete channel uses to targets and users, while beam adaptation selects transmit and receive beams with suitable directions, power levels, and beamwidths. Functionality selection determines whether each timeslot is used for sensing, communication, or their simultaneous operation, while user-target pairing specifies which users and targets are jointly served within the same timeslot. To ensure reliable operation, information imperfections arising from motion, quantization, feedback delays, and hardware limitations are considered. Resource economization is achieved by minimizing energy and time consumption through a multi-objective function, with strict prioritization of time savings. The resulting RRM problem is formulated as a semi-infinite, nonconvex mixed-integer nonlinear program (MINLP). Given the lack of generic methods for solving such problems, we propose a tailor-made approach that exploits the underlying structure of the problem to uncover hidden convexities. This enables an exact reformulation as a mixed-integer semidefinite program (MISDP), which can be solved to global optimality. Simulations reveal important interdependencies among the considered RRM components and show that the proposed approach achieves substantial performance improvements over baseline schemes, with gains up to 88%.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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