论文标题
Min-Max潜伏期优化基于感知的位置状态信息在车辆互联网中
Min-Max Latency Optimization Based on Sensed Position State Information in Internet of Vehicles
论文作者
论文摘要
双功能雷达通信（DFRC）是车辆Internet（IOV）中的必不可少的技术。考虑到路边单元（RSU）使用DFRC信号来感知车辆的位置状态信息（PSI），并根据PSI与车辆进行通信。本文的目的是通过考虑车辆PSI的估计精度约束和RSU的传输功率约束来最大程度地减少所有车辆之间的最大通信延迟。通过利用凸优化理论，提出了两种具有不同复杂性和适用场景的迭代功率分配算法。仿真结果表明，与其他方案相比，所提出的功率分配算法会收敛，并且可以显着减少车辆之间的最大发射延迟。
The dual-function radar communication (DFRC) is an essential technology in Internet of Vehicles (IoV). Consider that the road-side unit (RSU) employs the DFRC signals to sense the vehicles' position state information (PSI), and communicates with the vehicles based on PSI. The objective of this paper is to minimize the maximum communication delay among all vehicles by considering the estimation accuracy constraint of the vehicles' PSI and the transmit power constraint of RSU. By leveraging convex optimization theory, two iterative power allocation algorithms are proposed with different complexities and applicable scenarios. Simulation results indicate that the proposed power allocation algorithm converges and can significantly reduce the maximum transmit delay among vehicles compared with other schemes.
