基于非对称时间戳交换的贝叶斯联合同步与定位
Bayesian Joint Synchronization and Localization Based on Asymmetric Time-stamp Exchange
摘要：
在这项工作中，我们研究了超密集网络中的移动节点（MN）的联合同步和定位（sync&loc）。特别是，我们部署了MN和接入节点（AN）之间的非对称时间戳交换机制，传统上，为我们提供有关MN的时钟偏移和偏斜的信息。然而，有关AN和MN之间距离的信息也是交换时间戳所经历的传播延迟所固有的。此外，我们利用到达角（AoA）估计来确定时间戳交换数据包的传入方向，这给出了关于MN的位置的进一步信息。最后，我们采用贝叶斯递归滤波（BRF）结合上述信息，并联合估计MN的位置和时钟参数。仿真结果表明，该算法的位置和钟差估计的均方根误差分别小于1m和1ns。
英文摘要：
In this work, we study the joint synchronization and localization (sync&loc) of Mobile Nodes (MNs) in ultra dense networks. In particular, we deploy an asymmetric timestamp exchange mechanism between MNs and Access Nodes (ANs), that, traditionally, provides us with information about the MNs' clock offset and skew. However, information about the distance between an AN and a MN is also intrinsic to the propagation delay experienced by exchanged time-stamps. In addition, we utilize Angle of Arrival (AoA) estimation to determine the incoming direction of time-stamp exchange packets, which gives further information about the MNs' location. Finally, we employ Bayesian Recursive Filtering (BRF) to combine the aforementioned pieces of information and jointly estimate the position and clock parameters of MNs. The simulation results indicate that the Root Mean Square Errors (RMSEs) of position and clock offset estimation are kept below 1 meter and 1 ns, respectively.
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