X波段无人机协同车路系统，动态分配感知与通信时间
X-Band UAV-enabled Integrated Sensing and Communications for Vehicular Networks
- 基于双阴影信道模型，优化无人机感知与通信时间分配
- 在保证最低通信速率和感知可靠性下，实现性能平衡
- 适用于智能交通中复杂城市环境下的车路协同场景
无人飞行器（UAV）正被视为可同时提供感知与通信服务的空中平台，是智能交通系统的重要发展方向。本文研究了工作于X波段的无人机增强型集成感知与通信（ISaC）系统在车路网络中的最优时隙分配问题。考虑实际无人机约束及信道衰落影响，分析了感知精度与通信性能之间的权衡，采用单阴影与双阴影信道模型进行建模。提出一种优化框架，在确保最低通信速率与足够感知可靠性条件下，动态分配感知与通信时间。仿真结果表明，该策略能根据无人机-地面链路状况与目标距离自适应调整时间分配，有效协调智能出行场景中的感知与通信需求。
原文摘要 · Abstract (English)
Uncrewed aerial vehicles (UAVs) are increasingly considered as aerial platforms capable of providing both sensing and communication services, representing a promising paradigm for intelligent transportation systems. This paper investigates the optimal time allocation for a UAV-enabled integrated sensing and communication (ISaC) system operating in the X-band for vehicular networks. We analyze the trade-off between sensing accuracy and communication performance under practical UAV constraints and fading effects, considering both single-shadowing and double-shadowing channel models. An optimization framework is developed to allocate time between sensing and communication while guaranteeing minimum communication rates and sufficient sensing reliability. Simulation results demonstrate adaptive time allocation strategies, highlighting how UAV-to-ground channel conditions and target distances influence the balance between sensing and communication in smart mobility scenarios.
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