论文标题
部分可观测时空混沌系统的无模型预测
Envision of mmWave Wireless Communication with Artificial Intelligence
论文作者
论文摘要
储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。
The future wireless communication system faces the bottleneck of the shortage of traditional spectrum resources and the explosive growth of the demand for wireless services. Millimeter-wave communication with spectral resources has become an effective choice for the next generation of wireless broadband cellular communication. However, the transmission path loss is large and oxygen and water molecules absorb Characteristics such as seriousness have brought great challenges to millimeter wave communication, and it is necessary to seek a technical approach different from low-frequency wireless communication. In the analysis of millimeter wave transmission characteristics After the analysis, the research progress of millimeter wave communication technology and the RF front-end is comprehensively analyzed, and the technology of millimeter wave communication is thoroughly analyzed with technical challenges and proposed corresponding research directions. Finally, the advances of artificial intelligence and machine learning are also applied into millimeter wave communication, so we also cover these parts in this paper.