在adhoc ICAS网络中使用双阶段Kuramoto方法实现同步与定位
Synchronization and Localization in Ad-Hoc ICAS Networks Using a Two-Stage Kuramoto Method
AI总结：
本文提出一种分布式同步与定位方案，适用于车联网中的ICAS通信，通过双阶段Kuramoto方法实现频率和相位同步，并缓解有限采样频率对性能的影响。
摘要：
为在点对点车联网中实现集成通信与感知（ICAS），通信实体之间的频率和相位精确同步是必需的。此外，自动驾驶汽车需要准确估计周围车辆的位置。本文提出了一种联合的分布式同步与定位方案，适用于通信实体网络。我们的方案主要信号无关，因此可以应用于各种可能的ICAS信号。我们还缓解了有限采样频率的影响，否则会严重降劣同步和定位性能。
英文摘要：
To enable Integrated Communications and Sensing (ICAS) in a peer-to-peer vehicular network, precise synchronization in frequency and phase among the communicating entities is required. In addition, self-driving cars need accurate position estimates of the surrounding vehicles. In this work, we propose a joint, distributed synchronization and localization scheme for a network of communicating entities. Our proposed scheme is mostly signal-agnostic and therefore can be applied to a wide range of possible ICAS signals. We also mitigate the effect of finite sampling frequencies, which otherwise would degrade the synchronization and localization performance severely.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
