论文标题

Hermite-Gaussian模式相干组成的状态和基于深度学习的自由空间光学通信链接

Hermite-Gaussian-mode coherently composed states and deep learning based free-space optical communication link

论文作者

Zhang, Zilong, Zhao, Suyi, He, Wei, Gao, Yuan, Wang, Xin, Jie, Yuchen, Li, Xiaotian, Wang, Yuqi, Zhao, Changming

论文摘要

在基于激光的自由空间光学通信中,除了OAM梁,Hermite-Gaussian(HG)模式或HG模式相干组成的状态(HG-MCC)也可以作为信息载体,以扩展通道容量,并使用基于空间模式的编码和解码链路扩展通道容量。 HG-MCC的光场主要由三个独立参数确定,包括HG模式的索引,两个本本征模之间的相对初始阶段以及本征码的比例系数,可以在低模式顺序获得大量有效的编码模式。 HG-MCCS的光束强度分布具有明显的可区分空间特性,并且可以保持传播不变性,这很方便地通过基于卷积的神经网络(CNN)的图像识别方法来解码。我们通过实验利用HG-MCC来实现通信链接,包括编码,大气湍流(AT)下的传输以及基于CNN的解码。在六个内的本征码的索引顺序中,生成了125个HG-MCC并用于信息编码,并且对于非AT条件,平均识别精度达到了99.5%。对于125级颜色图像的传输,即使在条件下,系统的错误率也小于1.8%。我们的工作为密集数据通信和人工智能技术的未来组合提供了有用的基础。

In laser-based free-space optical communication, besides OAM beams, Hermite-Gaussian (HG) modes or HG-mode coherently composed states (HG-MCCS) can also be adopted as the information carrier to extend the channel capacity with the spatial pattern based encoding and decoding link. The light field of HG-MCCS is mainly determined by three independent parameters, including indexes of HG modes, relative initial phases between two eigenmodes, and scale coefficients of the eigenmodes, which can obtain a large number of effective coding modes at a low mode order. The beam intensity distributions of the HG-MCCSs have obvious distinguishable spatial characteristics and can keep propagation invariance, which are convenient to be decoded by the convolutional neural network (CNN) based image recognition method. We experimentally utilize HG-MCCS to realize a communication link including encoding, transmission under atmospheric turbulence (AT), and decoding based on CNN. With the index order of eigenmodes within six, 125 HG-MCCS are generated and used for information encoding, and the average recognition accuracy reached 99.5% for non-AT conditions. For the 125-level color images transmission, the error rate of the system is less than 1.8% even under the weak AT condition. Our work provides a useful basis for the future combination of dense data communication and artificial intelligence technology.

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