资源分配和轨迹规划在集成传感和通讯启用无人机辅助车辆网络中.
Mingyang Song1, Wenyang Zhang1, Jingpan Bai2,3,4,5
1School of Computer & Information Engineering, Anyang Normal University, Anyang 455000, China.
Sensors (Basel, Switzerland)
|December 11, 2025
概括
这项研究优化了无人驾驶飞行器 (UAV) 网络,在雷达传感极限下实现更好的通信速度. 拟议的算法通过平衡通信和传感性能来提高平均可实现率.
科学领域:
- 无线通信无线通信
- 网络工程 网络工程
- 信号处理 信号处理
背景情况:
- 车辆网络在提供高数据速率和可靠的传感服务方面面临着挑战.
- 综合传感和通信 (ISAC) 技术为无人机辅助网络提供了一个有前途的解决方案.
- 在无人机辅助车辆网络中平衡通信和传感性能对于高效的资源利用至关重要.
研究的目的:
- 用ISAC技术在无人机辅助的车辆网络中最大限度地提高平均可实现的通信速率.
- 为了解决复杂的优化问题,涉及无人机轨迹,车辆协会和雷达传感约束下的子频道分配.
- 开发一种高效的算法,以共同优化无人机-ISAC系统中的通信和传感.
主要方法:
- 制定了混合整数非线性程序 (MINLP) 的问题,考虑通信和感知性能权衡.
- 提出了一个基于区块坐标下降 (BCD) 的代算法,将MINLP分解为可解决的子问题.
- 采用连续凸近似 (SCA) 和凸优化技术来代地解决子问题.
主要成果:
- 提出的基于BCD的算法有效优化无人机轨迹,车辆协会和子频道分配.
- 与传统方法相比,模拟结果表明,平均可实现速率的性能优于传统方法.
- 该算法在雷达传感限制下成功平衡了通信和传感性能.
结论:
- 开发的代算法为在无人机辅助的ISAC车辆网络中最大化平均可实现速率提供了有效的解决方案.
- 拟议的方法在遵守传感要求的同时,与现有方法相比,显著提高了性能.
- 这项研究有助于在未来的综合传感和通信系统中推进高效的资源管理.
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