发表机构
School of Engineering, University of Glasgow（格拉斯哥大学工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对无人机ISAC系统中感知链路动态遮挡导致的功率浪费问题，提出感知中断感知型保形鲁棒功率分配框架，可降低约束违反率并节省功率。
AI 中文摘要
集成感知与通信（ISAC）基础设施可为空中机器人提供外部感知层，但动态遮挡会导致下一更新时刻的有效感知链路集合不确定。单一预测的可用性模式可能遗漏低信息结果，而保护所有模式会浪费功率，且当所有链路被遮挡时可能变得不可行。针对多基站（BS）无人机跟踪，我们提出一种感知中断感知型保形鲁棒功率分配框架。基于历史信息的联合预测器将雷达与跟踪历史映射到下一时刻的可用性概率，自适应预测集保留合理的相关模式。仅对保留的非中断模式施加跟踪约束，而全遮挡模式作为物理感知中断单独处理。在每个时隙的波束方向固定的情况下，所得标量功率分配为半定规划。可靠性界将可服务时隙的跟踪失败与部署策略的覆盖不足及优化不可行性关联起来。在5个随机种子的配对闭环仿真中，该方法实现了0.01%的可服务时隙约束违反率，且比保护所有非中断模式的方案节省47.0%的功率。
英文摘要
Integrated sensing and communications (ISAC) infrastructure can provide an external perception layer for aerial robots, but dynamic blockage makes the set of informative sensing links at the next update uncertain. A single predicted availability pattern can miss low-information outcomes, whereas protecting all patterns wastes power and may become infeasible when all links are blocked. We propose an outage-aware conformal robust power-allocation framework for multi-BS UAV tracking. A history-aware joint predictor maps radar and tracking histories to next-slot availability probabilities, and adaptive prediction sets retain plausible correlated patterns. Tracking constraints are enforced only for retained non-outage patterns, while the all-blocked pattern is treated separately as a physical sensing outage. With per-slot beam directions fixed, the resulting scalar-power allocation is a semidefinite program. A reliability bound relates serviceable-slot tracking failure to deployed-policy miscoverage and optimization infeasibility. Across paired closed-loop simulations over five random seeds, the method attains a 0.01% serviceable-slot constraint-violation rate and uses 47.0% less power than protection over all non-outage patterns.
Comments6 pages, 3 figures
