Synchronization and Localization in Ad-Hoc ICAS Networks Using a Two-Stage Kuramoto Method
This work addresses the need for precise synchronization and localization in peer-to-peer vehicular ICAS networks, which is critical for autonomous driving applications.
The paper proposes a joint distributed synchronization and localization scheme for ad-hoc ICAS networks using a two-stage Kuramoto method, achieving improved performance by mitigating finite sampling frequency effects.
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.