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基于CPWM和卷积神经网络的非视距光学相机通信

Non-line-of-sight optical camera communications based on CPWM and a convolutional neural network.

作者信息

Wan Xiangyu, Lin Bangjiang, Ghassemlooy Zabih, Huang Tianming, Luo Jiabin, Ding Yongqi

出版信息

Appl Opt. 2023 Oct 1;62(28):7367-7372. doi: 10.1364/AO.499844.

Abstract

Non-line-of-sight (NLOS) optical camera communications (OCC) exhibit greater link availability and mobility than line-of-sight links, which are more susceptible to blocking and shadowing. In this work, we propose an NLOS OCC system, where the data signal is mapped into color pulse width modulation (CPWM) symbols prior to transmission using a red-, green-, and blue light-emitting diode. A convolutional-neural-network-based receiver is used to demodulate the CPWM signal. Based on experimental results, the proposed scheme effectively mitigates the effects of diffuse reflection induced intersymbol interference, resulting in an increased data transmission rate to 7.2 kbps over a link span of more than 2 m, which is typical for indoor applications.

摘要

非视距(NLOS)光学相机通信(OCC)比视距链路具有更高的链路可用性和移动性,视距链路更容易受到阻挡和阴影的影响。在这项工作中,我们提出了一种非视距OCC系统,其中数据信号在使用红色、绿色和蓝色发光二极管进行传输之前被映射为彩色脉冲宽度调制(CPWM)符号。基于卷积神经网络的接收器用于解调CPWM信号。根据实验结果,所提出的方案有效地减轻了漫反射引起的码间干扰的影响,在超过2米的链路跨度上实现了高达7.2 kbps的数据传输速率提升,这对于室内应用来说是很典型的。

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