论文标题
无线网络中具有异质噪声来源的无线网络同步的神经方法
A neural approach to synchronization in wireless networks with heterogeneous sources of noise
论文作者
论文摘要
本文解决了存在影响同步质量的因素的情况下时钟同步的状态估计。例子是温度变化和延迟不对称。这些工作条件使同步在许多无线环境（例如无线传感器网络或WiFi）中成为具有挑战性的问题。研究动态状态估计是因为要克服非平稳的噪声至关重要。双向正时消息交换同步协议已作为参考。没有在随机环境上做出A-Priori假设，也没有执行温度测量。该算法是明确指定的离线，而无需调整一些参数以依赖工作条件。提出的方法表明，在传输路径中的一系列温度变化，不同的延迟分布和不对称水平具有鲁棒性。
The paper addresses state estimation for clock synchronization in the presence of factors affecting the quality of synchronization. Examples are temperature variations and delay asymmetry. These working conditions make synchronization a challenging problem in many wireless environments, such as Wireless Sensor Networks or WiFi. Dynamic state estimation is investigated as it is essential to overcome non-stationary noises. The two-way timing message exchange synchronization protocol has been taken as a reference. No a-priori assumptions are made on the stochastic environments and no temperature measurement is executed. The algorithms are unequivocally specified offline, without the need of tuning some parameters in dependence of the working conditions. The presented approach reveals to be robust to a large set of temperature variations, different delay distributions and levels of asymmetry in the transmission path.
