论文标题
5G中的同步：贝叶斯方法
Synchronization in 5G: a Bayesian Approach
论文作者
论文摘要
在这项工作中，我们提出了一种混合方法来同步大规模网络。特别是，我们利用Kalman过滤（KF）以及由Precision Time协议（PTP）生成的时间戳记，用于成对节点同步。此外，我们在实现高精度端到端网络同步时研究了因子图（FGS）以及信念传播（BP）算法的优点。最后，我们提出了将大规模网络分为局部同步域的想法，用于使用合适的同步算法。模拟结果表明，尽管混合方法简化了，但偏移估计中的误差仍低于5 ns。
In this work, we propose a hybrid approach to synchronize large scale networks. In particular, we draw on Kalman Filtering (KF) along with time-stamps generated by the Precision Time Protocol (PTP) for pairwise node synchronization. Furthermore, we investigate the merit of Factor Graphs (FGs) along with Belief Propagation (BP) algorithm in achieving high precision end-to-end network synchronization. Finally, we present the idea of dividing the large-scale network into local synchronization domains, for each of which a suitable sync algorithm is utilized. The simulation results indicate that, despite the simplifications in the hybrid approach, the error in the offset estimation remains below 5 ns.
