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%.

翻译：本文研究下行链路集成感知与通信（ISAC）系统的无线资源管理（RRM）设计，在信息不完美的条件下，联合优化时隙分配、波束适配、功能选择与用户-目标配对，以实现资源消耗的经济化。时隙分配为各目标与用户分配离散的信道使用次数；波束适配则选择具有合适方向、功率水平与波束宽度的发射与接收波束。功能选择决定每个时隙是用于感知、通信还是二者同时进行；用户-目标配对则指定在同一时隙内联合服务的用户与目标。为确保可靠运行，本文考虑了由运动、量化、反馈延迟及硬件限制引起的信息不完美性。资源经济化通过一个多目标函数实现，以最小化能量与时间消耗，并严格优先考虑节省时间。由此产生的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）。鉴于缺乏求解此类问题的通用方法，我们提出一种定制化方法，利用问题的内在结构以揭示隐藏的凸性。这使得问题能够精确重构为一个混合整数半定规划（MISDP），从而可求得全局最优解。仿真结果揭示了所考虑的RRM各组件间的重要相互依赖关系，并表明所提方法相较于基准方案实现了显著的性能提升，增益最高可达88%。